- home
- Advanced Search
- COVID-19
- Publications
- Research data
- Conference object
- EU
- arXiv.org e-Print Archive
- Mémoires en Sciences de l'Informati...
- COVID-19
- Publications
- Research data
- Conference object
- EU
- arXiv.org e-Print Archive
- Mémoires en Sciences de l'Informati...
Loading
description Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Publisher:ACM Funded by:EC | SoBigData-PlusPlusEC| SoBigData-PlusPlusAuthors: Shakshi Sharma; Anwitaman Datta; Vigneshwaran Shankaran; Rajesh Sharma;Shakshi Sharma; Anwitaman Datta; Vigneshwaran Shankaran; Rajesh Sharma;We demonstrate the Misinformation Concierge, a proof-of-concept that provides actionable intelligence on misinformation prevalent in social media. Specifically, it uses language processing and machine learning tools to identify subtopics of discourse and discern non/misleading posts; presents statistical reports for policy-makers to understand the big picture of prevalent misinformation in a timely manner; and recommends rebuttal messages for specific pieces of misinformation, identified from within the corpus of data - providing means to intervene and counter misinformation promptly. The Misinformation Concierge proof-of-concept using a curated dataset is accessible at: https://demo-frontend-uy34.onrender.com/ Comment: This is a preprinted version of our CIKM paper. Please cite our CIKM paper
arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3583780.3614746&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3583780.3614746&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2023 FrancePublisher:ISMRM Funded by:EC | NICI, ANR | PRIMESEC| NICI ,ANR| PRIMESNaëgel, Antoine; Karkouri, Jabrane; Ratiney, Helene; Kennouche, Djahid; Royer, Nicolas; Millet, Guillaume; Slade, Jill; Morel, Jérôme; Croisille, P; Viallon, Magalie;doi: 10.58530/2022/1021
Dynamic 31P MRS was performed during a standardized exercise of the lower leg, in patients with chronic fatigue enrolled in 2 clinical studies: multiple sclerosis patients and COVID19 patients that were hospitalized in intensive care unit and requiring respiratory assistance. In this work, we also revisit certain assumptions on the metabolite T1 and question shortcuts often made to shorten 31P protocol for a better patient’s compliance.
Hyper Article en Lig... arrow_drop_down Hyper Article en Ligne; HAL-Inserm; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2022Full-Text: https://hal.science/hal-03770519/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.58530/2022/1021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down Hyper Article en Ligne; HAL-Inserm; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2022Full-Text: https://hal.science/hal-03770519/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.58530/2022/1021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article , Preprint 2023Publisher:ACM Funded by:EC | PILLAR-RobotsEC| PILLAR-RobotsAuthors: Nikolaos Kegkeroglou; Panagiotis P. Filntisis; Petros Maragos;Nikolaos Kegkeroglou; Panagiotis P. Filntisis; Petros Maragos;The COVID-19 pandemic has undoubtedly changed the standards and affected all aspects of our lives, especially social communication. It has forced people to extensively wear medical face masks, in order to prevent transmission. This face occlusion can strongly irritate emotional reading from the face and urges us to incorporate the whole body as an emotional cue. In this paper, we conduct insightful studies about the effect of face occlusion on emotion recognition performance, and showcase the superiority of full body input over the plain masked face. We utilize a deep learning model based on the Temporal Segment Network framework, and aspire to fully overcome the face mask consequences. Although facial and bodily features can be learned from a single input, this may lead to irrelevant information confusion. By processing those features separately and fusing their prediction scores, we are more effectively taking advantage of both modalities. This framework also naturally supports temporal modeling, by mingling information among neighboring frames. In combination, these techniques form an effective system capable of tackling emotion recognition difficulties, caused by safety protocols applied in crucial areas. Comment: 8 pages
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3594806.3594829&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3594806.3594829&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Publisher:ACM Funded by:EC | AI4MediaEC| AI4MediaAuthors: David Alonso del Barrio; Daniel Gatica-Perez;David Alonso del Barrio; Daniel Gatica-Perez;Identifying the frames of news is important to understand the articles' vision, intention, message to be conveyed, and which aspects of the news are emphasized. Framing is a widely studied concept in journalism, and has emerged as a new topic in computing, with the potential to automate processes and facilitate the work of journalism professionals. In this paper, we study this issue with articles related to the Covid-19 anti-vaccine movement. First, to understand the perspectives used to treat this theme, we developed a protocol for human labeling of frames for 1786 headlines of No-Vax movement articles of European newspapers from 5 countries. Headlines are key units in the written press, and worth of analysis as many people only read headlines (or use them to guide their decision for further reading.) Second, considering advances in Natural Language Processing (NLP) with large language models, we investigated two approaches for frame inference of news headlines: first with a GPT-3.5 fine-tuning approach, and second with GPT-3.5 prompt-engineering. Our work contributes to the study and analysis of the performance that these models have to facilitate journalistic tasks like classification of frames, while understanding whether the models are able to replicate human perception in the identification of these frames.
ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3591106https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3591106.3592278&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!visibility 23visibility views 23 download downloads 50 Powered bymore_vert ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3591106https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3591106.3592278&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type , Preprint 2023 SwitzerlandPublisher:ACM Funded by:EC | AI4MediaEC| AI4MediaAuthors: David Alonso del Barrio; Daniel Gatica-Perez;David Alonso del Barrio; Daniel Gatica-Perez;This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine movement over a period of 22 months in 2020-2021, we used Natural Language Processing techniques including topic modeling, sentiment analysis, semantic relationship with word embeddings, political analysis, named entity recognition, and semantic networks, to understand the specific role of the European traditional press in the disinformation ecosystem. The results of this multi-angle analysis demonstrate that the European well-established press actively opposed a variety of hoaxes mainly spread on social media, and was critical of the anti-vax trend, regardless of the political orientation of the newspaper. This confirms the relevance of studying the role of high-quality press in the disinformation ecosystem.
ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3592572Infoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3592572.3592845&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!visibility 7visibility views 7 download downloads 27 Powered bymore_vert ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3592572Infoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3592572.3592845&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Conference object 2023Publisher:IEEE Funded by:EC | EAREC| EARAuthors: Xia, Tong; Han, Jing; Ghosh, Abhirup; Mascolo, Cecilia;Xia, Tong; Han, Jing; Ghosh, Abhirup; Mascolo, Cecilia;Federated learning (FL) aided health diagnostic models can incorporate data from a large number of personal edge devices (e.g., mobile phones) while keeping the data local to the originating devices, largely ensuring privacy. However, such a cross-device FL approach for health diagnostics still imposes many challenges due to both local data imbalance (as extreme as local data consists of a single disease class) and global data imbalance (the disease prevalence is generally low in a population). Since the federated server has no access to data distribution information, it is not trivial to solve the imbalance issue towards an unbiased model. In this paper, we propose FedLoss, a novel cross-device FL framework for health diagnostics. Here the federated server averages the models trained on edge devices according to the predictive loss on the local data, rather than using only the number of samples as weights. As the predictive loss better quantifies the data distribution at a device, FedLoss alleviates the impact of data imbalance. Through a real-world dataset on respiratory sound and symptom-based COVID-$19$ detection task, we validate the superiority of FedLoss. It achieves competitive COVID-$19$ detection performance compared to a centralised model with an AUC-ROC of $79\%$. It also outperforms the state-of-the-art FL baselines in sensitivity and convergence speed. Our work not only demonstrates the promise of federated COVID-$19$ detection but also paves the way to a plethora of mobile health model development in a privacy-preserving fashion. Comment: This paper has been accepted by IEEE ICASSP 2023
arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.1109/icassp...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icassp49357.2023.10096427&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.1109/icassp...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icassp49357.2023.10096427&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Contribution for newspaper or weekly magazine 2023 FrancePublisher:ACM Funded by:EC | CREATIV, EC | HumanE-AI-Net, EC | COMPUTEDEC| CREATIV ,EC| HumanE-AI-Net ,EC| COMPUTEDJoon Gi Shin; Janin Koch; Andrés Lucero; Peter Dalsgaard; Wendy E. Mackay;Workshop, Due to the COVID-19 pandemic, the event has been cancelled.; International audience; People can generate more innovative ideas when they collaborate with one another, collectively exploring ideas and exchanging viewpoints. Advancements in artificial intelligence have opened up new opportunities in people’s creative activities where individual users ideate with diverse forms of AI. For instance, AI agents and intelligent tools have been designed as ideation partners that provide inspiration, suggest ideation methods, or generate alternative ideas. However, what AI can bring to collaborative ideation among a group of users has not been fully understood. Compared to ideating with individuals, ideating with multiple users would require understanding users’ social interaction, transforming individual efforts into a group effort, and—in the end—making users satisfied that they collaborated with other group members. This workshop aims to bring together a community of researchers and practitioners to explore the integration of AI in human-human collaborative ideation. The exploration will center around identifying the potential roles of AI as well as the process and form of collaborative ideation, considering what users want to do with AI or humans.
PURE Aarhus Universi... arrow_drop_down PURE Aarhus UniversityContribution for newspaper or weekly magazine . 2023Data sources: PURE Aarhus UniversityPURE Aarhus UniversityContribution for newspaper or weekly magazine . Conference object . 2023 . Peer-reviewedHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2023License: CC BYHAL DescartesConference object . 2023Full-Text: https://hal.inria.fr/hal-04023507/documentData sources: HAL Descartesadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3544549.3573802&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert PURE Aarhus Universi... arrow_drop_down PURE Aarhus UniversityContribution for newspaper or weekly magazine . 2023Data sources: PURE Aarhus UniversityPURE Aarhus UniversityContribution for newspaper or weekly magazine . Conference object . 2023 . Peer-reviewedHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2023License: CC BYHAL DescartesConference object . 2023Full-Text: https://hal.inria.fr/hal-04023507/documentData sources: HAL Descartesadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3544549.3573802&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Publisher:IEEE Funded by:EC | PUZZLEEC| PUZZLEAuthors: Nefeli Bountouni; Sotiris Koussouris; Alexandros Vasileiou; Stylianos A. Kazazis;Nefeli Bountouni; Sotiris Koussouris; Alexandros Vasileiou; Stylianos A. Kazazis;The rapid digitalisation of SMEs, further expedited as a business continuity measure against Covid19 impact, has brought along major cybersecurity challenges, as it creates a fertile landscape for malicious actors, that want to capitalise on the insufficient cybersecurity planning and preparedness of SMEs to conduct low-effort, lucrative attacks. This paper constitutes a case study on the cybersecurity challenges, specificities and the safeguarding of the ATracker, a real-life data collection and analytics engine developed by the SME Suite5. The ATracker has been successfully protected against attacks in conjunction with the PUZZLE Framework, a holistic policy-based cybersecurity solution, addressing major cybersecurity pillars and leveraging on the latest scientific advancements in cybersecurity research. Comment: A modified version of this work has been submitted to the Workshop IOSEC 2023 in the context of the 2023 19th International Conference on the Design of Reliable Communication Networks (DRCN) and published in IEEE Xplore
ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/drcn57075.2023.10108247&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 33visibility views 33 download downloads 37 Powered bymore_vert ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/drcn57075.2023.10108247&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article , Conference object 2023 Czech Republic, Belgium, Finland, Germany, Italy, Norway, Portugal, Netherlands, Peru, Portugal, Poland, Germany, Portugal, United Kingdom, France, United Kingdom, Norway, Turkey, United Kingdom, PolandPublisher:Springer Science and Business Media LLC Funded by:NIH | OST DOCTORAL TRAINING IN ..., SSHRC, UKRI | Development of diagnostic... +3 projectsNIH| OST DOCTORAL TRAINING IN EMOTION RESEARCH ,SSHRC ,UKRI| Development of diagnostic device to differentiate between bipolar and unipolar depression ,ARC| Discovery Projects - Grant ID: DP180102384 ,UKRI| A Smart System to Empower Healthy Food Choices ,EC| JITSUVAXBuchanan, Erin M.; Lewis, Savannah C.; Paris, Bastien; Forscher, Patrick S.; Pavlacic, Jeffrey M.; Beshears, Julie E.; Drexler, Shira Meir; Gourdon-Kanhukamwe, Amélie; Mallik, Peter R.; Silan, Miguel Alejandro A.; Miller, Jeremy K.; IJzerman, Hans; Moshontz, Hannah; Beaudry, Jennifer L.; Suchow, Jordan W.; Chartier, Christopher R.; Coles, Nicholas A.; Sharifian, Mohammad Hasan; Todsen, Anna Louise; Levitan, Carmel A.; Azevedo, Flávio; Legate, Nicole; Heller, Blake; Rothman, Alexander J.; Dorison, Charles A.; Gill, Brian P.; Wang, Ke; Rees, Vaughan W.; Gibbs, Nancy; Goldenberg, Amit; Thi Nguyen, Thuy vy; Gross, James J.; Kaminski, Gwenaêl; von Bastian, Claudia C.; Paruzel-Czachura, Mariola; Mosannenzadeh, Farnaz; Azouaghe, Soufian; Bran, Alexandre; Ruiz-Fernandez, Susana; Santos, Anabela Caetano; Reggev, Niv; Zickfeld, Janis H.; Akkas, Handan; Pantazi, Myrto; Ropovik, Ivan; Korbmacher, Max; Arriaga, Patrícia; Gjoneska, Biljana; Warmelink, Lara; Alves, Sara G.; de Holanda Coelho, Gabriel Lins; Stieger, Stefan; Schei, Vidar; Hanel, Paul H.P.; Szaszi, Barnabas; Fedotov, Maksim; Antfolk, Jan; Marcu, Gabriela Mariana; Schrötter, Jana; Kunst, Jonas R.; Geiger, Sandra J.; Adetula, Adeyemi; Kocalar, Halil Emre; Kielińska, Julita; Kačmár, Pavol; Bokkour, Ahmed; Galindo-Caballero, Oscar J.; Djamai, Ikhlas; Pöntinen, Sara Johanna; Agesin, Bamikole Emmanuel; Jernsäther, Teodor; Urooj, Anum; Rachev, Nikolay R.; Koptjevskaja-Tamm, Maria; Kurfalı, Murathan; Pit, Ilse L.; Li, Ranran; Çoksan, Sami; Dubrov, Dmitrii; Paltrow, Tamar Elise; Baník, Gabriel; Korobova, Tatiana; Studzinska, Anna; Jiang, Xiaoming; Aruta, John Jamir Benzon R.; Vintr, Jáchym; Chiu, Faith; Kaliska, Lada; Berkessel, Jana B.; Tümer, Murat; Morales-Izquierdo, Sara; Chuan-Peng, Hu; Vezirian, Kevin; Rosa, Anna Dalla; Bialobrzeska, Olga; Vasilev, Martin R.; Beitner, Julia; Kácha, Ondřej; Žuro, Barbara; Westerlund, Minja; Nedelcheva-Datsova, Mina; Findor, Andrej; Krupić, Dajana; Kowal, Marta; Askelund, Adrian Dahl; Pourafshari, Razieh; Đorđević, Jasna Milošević; Schmidt, Nadya Daniela; Baklanova, Ekaterina; Szala, Anna; Zakharov, Ilya; Vranka, Marek A.; Ihaya, Keiko; Grano, Caterina; Cellini, Nicola; Białek, Michał; Anton-Boicuk, Lisa; Dalgar, Ilker; Adıgüzel, Arca; Verharen, Jeroen P.H.; Maturan, Princess Lovella G.; Kassianos, Angelos P.; Oliveira, Raquel; Čadek, Martin; Adoric, Vera Cubela; Özdoğru, Asil Ali; Sverdrup, Therese E.; Aczel, Balazs; Zambrano, Danilo; Ahmed, Afroja; Tamnes, Christian K.; Yamada, Yuki; Volz, Leonhard; Sunami, Naoyuki; Suter, Lilian; Vieira, Luc; Groyecka-Bernard, Agata; Kamburidis, Julia Arhondis; Reips, Ulf Dietrich; Harutyunyan, Mikayel; Adetula, Gabriel Agboola; Allred, Tara Bulut; Barzykowski, Krystian; Antazo, Benedict G.; Zsido, Andras N.; Šakan, Dušana Dušan; Cyrus-Lai, Wilson; Ahlgren, Lina Pernilla; Hruška, Matej; Vega, Diego; Manunta, Efisio; Mokady, Aviv; Capizzi, Mariagrazia; Martončik, Marcel; Say, Nicolas; Filip, Katarzyna; Vilar, Roosevelt; Staniaszek, Karolina; Vdovic, Milica; Adamkovic, Matus; Johannes, Niklas; Hajdu, Nandor; Cohen, Noga; Overkott, Clara; Krupić, Dino; Hubena, Barbora; Nilsonne, Gustav; Mioni, Giovanna; Solorzano, Claudio Singh; Ishii, Tatsunori; Chen, Zhang; Kushnir, Elizaveta; Karaarslan, Cemre; Ribeiro, Rafael R.; Khaoudi, Ahmed; Kossowska, Małgorzata; Bavolar, Jozef; Hoyer, Karlijn; Roczniewska, Marta; Karababa, Alper; Becker, Maja; Monteiro, Renan P.; Kunisato, Yoshihiko; Metin-Orta, Irem; Adamus, Sylwia; Kozma, Luca; Czarnek, Gabriela; Domurat, Artur; Štrukelj, Eva; Alvarez, Daniela Serrato; Parzuchowski, Michal; Massoni, Sébastien; Czamanski-Cohen, Johanna; Pronizius, Ekaterina; Muchembled, Fany; van Schie, Kevin; Saçaklı, Aslı; Hristova, Evgeniya; Kuzminska, Anna O.; Charyate, Abdelilah; Musser, Erica D.; Sirota, Miroslav; Ross, Robert M.; Foroni, Francesco; Almeida, Inês A.T.; Grigoryev, Dmitry; Lewis, David M.G.; Holford, Dawn L.; Janssen, Steve M.J.; Tatachari, Srinivasan; Batres, Carlota; Olofsson, Jonas K.; Belaus, Anabel; Pfuhl, Gerit; Corral-Frias, Nadia Sarai; Sousa, Daniela; Voracek, Martin; DeBruine, Lisa M.; Anne, Michele; Očovaj, Sanja Batić; Arvanitis, Alexios; Arinze, Nwadiogo Chisom; Bundt, Carsten; Lamm, Claus; Calin-Jageman, Robert J.; Karekla, Maria; Hricova, Monika; Koehn, Monica A.; Bai, Hui; Krafnick, Anthony J.; Lins, Samuel; Macapagal, Paulo Manuel L.; Szwed, Paulina; Zdybek, Przemysław Marcin; Tran, Ulrich S.; Albayrak-Aydemir, Nihan; Dixson, Barnaby James Wyld; Jaeger, Bastian; Butt, Muhammad Mussaffa; Sorokowska, Agnieszka; Willis, Megan L.; Stephen, Ian D.; de la Rosa-Gómez, Anabel; Sutherland, Clare A.M.; Behzadnia, Behzad; Ogbonnaya, Chisom Esther; Fu, Cynthia H.Y.; Rahal, Rima Maria; Hostler, Thomas J.; Khosla, Meetu; Lazarevic, Ljiljana B.; Luis, Elkin O.; Reeck, Crystal; Ryan, Richard M.; Travaglino, Giovanni A.; Chopik, William J.; Xiao, Qinyu; Verbruggen, Frederick;handle: 11250/3084711 , 20.500.12809/10543 , 2066/290924 , 20.500.11820/fd77e6a0-c291-42bc-9eb4-3c8be177815b , 1871.1/493d9e6f-23c0-408c-b085-5fb867ea7059 , 10216/148131 , 20.500.14178/2132 , 10451/56312 , 10071/28653 , 21.11116/0000-000D-FCE3-7 , 21.11116/0000-000D-FCE5-5 , 20.500.14178/2122 , 1854/LU-01HM8BT6M0E6FH11H697ZJCYD2
pmid: 36774440
pmc: PMC9918828
handle: 11250/3084711 , 20.500.12809/10543 , 2066/290924 , 20.500.11820/fd77e6a0-c291-42bc-9eb4-3c8be177815b , 1871.1/493d9e6f-23c0-408c-b085-5fb867ea7059 , 10216/148131 , 20.500.14178/2132 , 10451/56312 , 10071/28653 , 21.11116/0000-000D-FCE3-7 , 21.11116/0000-000D-FCE5-5 , 20.500.14178/2122 , 1854/LU-01HM8BT6M0E6FH11H697ZJCYD2
pmid: 36774440
pmc: PMC9918828
In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data. Funder: Horizon 2020 grant 964728 (JITSUVAX) from the European Commission and was supported by a United Kingdom Research and Innovation (UKRI) Research Fellowship grant ES/V011901/1 Funder: Program FUTURE LEADER of Lorraine Université d’Excellence within the program Investissements Avenir (ANR-15-IDEX-04-LUE) operated by the French National Research Agency Funder: Association Nationale de la Recherche et de la Technologie (National Association for Research and Technology); doi: https://doi.org/10.13039/501100003032 Funder: The work of Dmitrii Dubrov was supported within the framework of the Basic Research Program at HSE University, RF Funder: Rubicon grant (019.183SG.007) from the Netherlands Organization for Scientific Research (NWO) Funder: Agentúra na podporu výskumu a vývoja (Slovak Research and Development Agency) - APVV-17-0596 Funder: UID/PSI/03125/2019 from the Portuguese National Foundation for Science and Technology (FCT). Funder: Kingston University (Kingston University, London); doi: https://doi.org/10.13039/100010049 Funder: Association Nationale de la Recherche Scientifique and Pacifica (CIFRE grant 2017/0245) Funder: Statutory funds of the Institute of Psychology, University of Wroclaw Funder: PSA research grant ($285.59) for the PSACR projects data collection Funder: The Japan Society for the Promotion of Science KAKENHI [19K14370] Funder: Social Science and Humanities Research Council of Canada Funder: National Science Centre, Poland (2019/35/B/HS6/00528) Funder: Slovak Research and Development Agency - APVV-17-0596 Funder: The Institute of Psychology, Jagiellonian University Funder: JSPS KAKENHI Grant Numbers JP18K12015 and JP20H04581 Funder: University of Desarrollo, Faculty of Psychology Funder: IDN Being Human Lab (University of Wrocław) Funder: Dominican University Faculty Support Grant Funder: Vicerrectoria de Investigaciones, Uniandes Funder: Australian Research Council (DP180102384) Funder: Amazon Web Services (AWS) Imagine Grant Funder: HSE University Basic Research Program Funder: Progres Q18, Charles University Funder: ANID - Fondecyt 1201513 Funder: Huo Family Foundation Funder: PRIMUS/20/HUM/009 Funder: FONDECYT 1221538
NARCIS arrow_drop_down CU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMuğla Sıtkı Koçman Üniversitesi Kurumsal Akademik Arşiv SistemiConference object . 2023Ghent University Academic BibliographyArticle . 2023Data sources: Ghent University Academic BibliographyJyväskylä University Digital ArchiveArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Jyväskylä University Digital ArchiveUniversidade de Lisboa: Repositório.ULOther literature type . 2023License: CC BYData sources: Universidade de Lisboa: Repositório.ULRepositório Aberto da Universidade do PortoArticle . 2023Data sources: Repositório Aberto da Universidade do PortoCU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMémoires en Sciences de l'Information et de la CommunicationArticle . 2023Full-Text: https://hal.science/hal-04294810/documentHAL Paris Nanterre; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41597-022-01811-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!visibility 181visibility views 181 download downloads 123 Powered bymore_vert NARCIS arrow_drop_down CU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMuğla Sıtkı Koçman Üniversitesi Kurumsal Akademik Arşiv SistemiConference object . 2023Ghent University Academic BibliographyArticle . 2023Data sources: Ghent University Academic BibliographyJyväskylä University Digital ArchiveArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Jyväskylä University Digital ArchiveUniversidade de Lisboa: Repositório.ULOther literature type . 2023License: CC BYData sources: Universidade de Lisboa: Repositório.ULRepositório Aberto da Universidade do PortoArticle . 2023Data sources: Repositório Aberto da Universidade do PortoCU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMémoires en Sciences de l'Information et de la CommunicationArticle . 2023Full-Text: https://hal.science/hal-04294810/documentHAL Paris Nanterre; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41597-022-01811-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Embargo end date: 01 Jan 2023Publisher:arXiv Funded by:EC | DUSTEC| DUSTAuthors: Oswald, Yannick; Malleson, Nicolas; Suchak, Keiran;Oswald, Yannick; Malleson, Nicolas; Suchak, Keiran;Global problems, such as pandemics and climate change, require rapid international coordination and diffusion of policy. These phenomena are rare however, with one notable example being the international policy response to the COVID-19 pandemic in early 2020. Here we build an agent-based model of this rapid policy diffusion, where countries constitute the agents and with the principal mechanism for diffusion being peer mimicry. Since it is challenging to predict accurately the policy diffusion curve, we utilize data assimilation, that is an ``on-line'' feed of data to constrain the model against observations. The specific data assimilation algorithm we apply is a particle filter because of its convenient implementation, its ability to handle categorical variables and because the model is not overly computationally expensive, hence a more efficient algorithm is not required. We find that the model alone is able to predict the policy diffusion relatively well with an ensemble of at least 100 simulation runs. The particle filter however improves the fit to the data, reliably so from 500 runs upwards, and increasing filtering frequency results in improved prediction.
ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.48550/arxiv.2302.11277&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 40visibility views 40 download downloads 30 Powered bymore_vert ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.48550/arxiv.2302.11277&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
Loading
description Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Publisher:ACM Funded by:EC | SoBigData-PlusPlusEC| SoBigData-PlusPlusAuthors: Shakshi Sharma; Anwitaman Datta; Vigneshwaran Shankaran; Rajesh Sharma;Shakshi Sharma; Anwitaman Datta; Vigneshwaran Shankaran; Rajesh Sharma;We demonstrate the Misinformation Concierge, a proof-of-concept that provides actionable intelligence on misinformation prevalent in social media. Specifically, it uses language processing and machine learning tools to identify subtopics of discourse and discern non/misleading posts; presents statistical reports for policy-makers to understand the big picture of prevalent misinformation in a timely manner; and recommends rebuttal messages for specific pieces of misinformation, identified from within the corpus of data - providing means to intervene and counter misinformation promptly. The Misinformation Concierge proof-of-concept using a curated dataset is accessible at: https://demo-frontend-uy34.onrender.com/ Comment: This is a preprinted version of our CIKM paper. Please cite our CIKM paper
arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3583780.3614746&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3583780.3614746&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object 2023 FrancePublisher:ISMRM Funded by:EC | NICI, ANR | PRIMESEC| NICI ,ANR| PRIMESNaëgel, Antoine; Karkouri, Jabrane; Ratiney, Helene; Kennouche, Djahid; Royer, Nicolas; Millet, Guillaume; Slade, Jill; Morel, Jérôme; Croisille, P; Viallon, Magalie;doi: 10.58530/2022/1021
Dynamic 31P MRS was performed during a standardized exercise of the lower leg, in patients with chronic fatigue enrolled in 2 clinical studies: multiple sclerosis patients and COVID19 patients that were hospitalized in intensive care unit and requiring respiratory assistance. In this work, we also revisit certain assumptions on the metabolite T1 and question shortcuts often made to shorten 31P protocol for a better patient’s compliance.
Hyper Article en Lig... arrow_drop_down Hyper Article en Ligne; HAL-Inserm; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2022Full-Text: https://hal.science/hal-03770519/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.58530/2022/1021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down Hyper Article en Ligne; HAL-Inserm; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2022Full-Text: https://hal.science/hal-03770519/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.58530/2022/1021&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Article , Preprint 2023Publisher:ACM Funded by:EC | PILLAR-RobotsEC| PILLAR-RobotsAuthors: Nikolaos Kegkeroglou; Panagiotis P. Filntisis; Petros Maragos;Nikolaos Kegkeroglou; Panagiotis P. Filntisis; Petros Maragos;The COVID-19 pandemic has undoubtedly changed the standards and affected all aspects of our lives, especially social communication. It has forced people to extensively wear medical face masks, in order to prevent transmission. This face occlusion can strongly irritate emotional reading from the face and urges us to incorporate the whole body as an emotional cue. In this paper, we conduct insightful studies about the effect of face occlusion on emotion recognition performance, and showcase the superiority of full body input over the plain masked face. We utilize a deep learning model based on the Temporal Segment Network framework, and aspire to fully overcome the face mask consequences. Although facial and bodily features can be learned from a single input, this may lead to irrelevant information confusion. By processing those features separately and fusing their prediction scores, we are more effectively taking advantage of both modalities. This framework also naturally supports temporal modeling, by mingling information among neighboring frames. In combination, these techniques form an effective system capable of tackling emotion recognition difficulties, caused by safety protocols applied in crucial areas. Comment: 8 pages
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3594806.3594829&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3594806.3594829&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Publisher:ACM Funded by:EC | AI4MediaEC| AI4MediaAuthors: David Alonso del Barrio; Daniel Gatica-Perez;David Alonso del Barrio; Daniel Gatica-Perez;Identifying the frames of news is important to understand the articles' vision, intention, message to be conveyed, and which aspects of the news are emphasized. Framing is a widely studied concept in journalism, and has emerged as a new topic in computing, with the potential to automate processes and facilitate the work of journalism professionals. In this paper, we study this issue with articles related to the Covid-19 anti-vaccine movement. First, to understand the perspectives used to treat this theme, we developed a protocol for human labeling of frames for 1786 headlines of No-Vax movement articles of European newspapers from 5 countries. Headlines are key units in the written press, and worth of analysis as many people only read headlines (or use them to guide their decision for further reading.) Second, considering advances in Natural Language Processing (NLP) with large language models, we investigated two approaches for frame inference of news headlines: first with a GPT-3.5 fine-tuning approach, and second with GPT-3.5 prompt-engineering. Our work contributes to the study and analysis of the performance that these models have to facilitate journalistic tasks like classification of frames, while understanding whether the models are able to replicate human perception in the identification of these frames.
ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3591106https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3591106.3592278&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!visibility 23visibility views 23 download downloads 50 Powered bymore_vert ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3591106https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3591106.3592278&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Other literature type , Preprint 2023 SwitzerlandPublisher:ACM Funded by:EC | AI4MediaEC| AI4MediaAuthors: David Alonso del Barrio; Daniel Gatica-Perez;David Alonso del Barrio; Daniel Gatica-Perez;This paper examines how the European press dealt with the no-vax reactions against the Covid-19 vaccine and the dis- and misinformation associated with this movement. Using a curated dataset of 1786 articles from 19 European newspapers on the anti-vaccine movement over a period of 22 months in 2020-2021, we used Natural Language Processing techniques including topic modeling, sentiment analysis, semantic relationship with word embeddings, political analysis, named entity recognition, and semantic networks, to understand the specific role of the European traditional press in the disinformation ecosystem. The results of this multi-angle analysis demonstrate that the European well-established press actively opposed a variety of hoaxes mainly spread on social media, and was critical of the anti-vax trend, regardless of the political orientation of the newspaper. This confirms the relevance of studying the role of high-quality press in the disinformation ecosystem.
ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3592572Infoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3592572.3592845&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!visibility 7visibility views 7 download downloads 27 Powered bymore_vert ZENODO arrow_drop_down ZENODOConference object . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://dl.acm.org/doi/pdf/10.1145/3592572Infoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3592572.3592845&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Conference object 2023Publisher:IEEE Funded by:EC | EAREC| EARAuthors: Xia, Tong; Han, Jing; Ghosh, Abhirup; Mascolo, Cecilia;Xia, Tong; Han, Jing; Ghosh, Abhirup; Mascolo, Cecilia;Federated learning (FL) aided health diagnostic models can incorporate data from a large number of personal edge devices (e.g., mobile phones) while keeping the data local to the originating devices, largely ensuring privacy. However, such a cross-device FL approach for health diagnostics still imposes many challenges due to both local data imbalance (as extreme as local data consists of a single disease class) and global data imbalance (the disease prevalence is generally low in a population). Since the federated server has no access to data distribution information, it is not trivial to solve the imbalance issue towards an unbiased model. In this paper, we propose FedLoss, a novel cross-device FL framework for health diagnostics. Here the federated server averages the models trained on edge devices according to the predictive loss on the local data, rather than using only the number of samples as weights. As the predictive loss better quantifies the data distribution at a device, FedLoss alleviates the impact of data imbalance. Through a real-world dataset on respiratory sound and symptom-based COVID-$19$ detection task, we validate the superiority of FedLoss. It achieves competitive COVID-$19$ detection performance compared to a centralised model with an AUC-ROC of $79\%$. It also outperforms the state-of-the-art FL baselines in sensitivity and convergence speed. Our work not only demonstrates the promise of federated COVID-$19$ detection but also paves the way to a plethora of mobile health model development in a privacy-preserving fashion. Comment: This paper has been accepted by IEEE ICASSP 2023
arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.1109/icassp...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icassp49357.2023.10096427&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down https://doi.org/10.1109/icassp...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: Crossrefhttps://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/icassp49357.2023.10096427&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Contribution for newspaper or weekly magazine 2023 FrancePublisher:ACM Funded by:EC | CREATIV, EC | HumanE-AI-Net, EC | COMPUTEDEC| CREATIV ,EC| HumanE-AI-Net ,EC| COMPUTEDJoon Gi Shin; Janin Koch; Andrés Lucero; Peter Dalsgaard; Wendy E. Mackay;Workshop, Due to the COVID-19 pandemic, the event has been cancelled.; International audience; People can generate more innovative ideas when they collaborate with one another, collectively exploring ideas and exchanging viewpoints. Advancements in artificial intelligence have opened up new opportunities in people’s creative activities where individual users ideate with diverse forms of AI. For instance, AI agents and intelligent tools have been designed as ideation partners that provide inspiration, suggest ideation methods, or generate alternative ideas. However, what AI can bring to collaborative ideation among a group of users has not been fully understood. Compared to ideating with individuals, ideating with multiple users would require understanding users’ social interaction, transforming individual efforts into a group effort, and—in the end—making users satisfied that they collaborated with other group members. This workshop aims to bring together a community of researchers and practitioners to explore the integration of AI in human-human collaborative ideation. The exploration will center around identifying the potential roles of AI as well as the process and form of collaborative ideation, considering what users want to do with AI or humans.
PURE Aarhus Universi... arrow_drop_down PURE Aarhus UniversityContribution for newspaper or weekly magazine . 2023Data sources: PURE Aarhus UniversityPURE Aarhus UniversityContribution for newspaper or weekly magazine . Conference object . 2023 . Peer-reviewedHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2023License: CC BYHAL DescartesConference object . 2023Full-Text: https://hal.inria.fr/hal-04023507/documentData sources: HAL Descartesadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3544549.3573802&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert PURE Aarhus Universi... arrow_drop_down PURE Aarhus UniversityContribution for newspaper or weekly magazine . 2023Data sources: PURE Aarhus UniversityPURE Aarhus UniversityContribution for newspaper or weekly magazine . Conference object . 2023 . Peer-reviewedHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2023License: CC BYHAL DescartesConference object . 2023Full-Text: https://hal.inria.fr/hal-04023507/documentData sources: HAL Descartesadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1145/3544549.3573802&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Publisher:IEEE Funded by:EC | PUZZLEEC| PUZZLEAuthors: Nefeli Bountouni; Sotiris Koussouris; Alexandros Vasileiou; Stylianos A. Kazazis;Nefeli Bountouni; Sotiris Koussouris; Alexandros Vasileiou; Stylianos A. Kazazis;The rapid digitalisation of SMEs, further expedited as a business continuity measure against Covid19 impact, has brought along major cybersecurity challenges, as it creates a fertile landscape for malicious actors, that want to capitalise on the insufficient cybersecurity planning and preparedness of SMEs to conduct low-effort, lucrative attacks. This paper constitutes a case study on the cybersecurity challenges, specificities and the safeguarding of the ATracker, a real-life data collection and analytics engine developed by the SME Suite5. The ATracker has been successfully protected against attacks in conjunction with the PUZZLE Framework, a holistic policy-based cybersecurity solution, addressing major cybersecurity pillars and leveraging on the latest scientific advancements in cybersecurity research. Comment: A modified version of this work has been submitted to the Workshop IOSEC 2023 in the context of the 2023 19th International Conference on the Design of Reliable Communication Networks (DRCN) and published in IEEE Xplore
ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/drcn57075.2023.10108247&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 33visibility views 33 download downloads 37 Powered bymore_vert ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/drcn57075.2023.10108247&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Other literature type , Article , Conference object 2023 Czech Republic, Belgium, Finland, Germany, Italy, Norway, Portugal, Netherlands, Peru, Portugal, Poland, Germany, Portugal, United Kingdom, France, United Kingdom, Norway, Turkey, United Kingdom, PolandPublisher:Springer Science and Business Media LLC Funded by:NIH | OST DOCTORAL TRAINING IN ..., SSHRC, UKRI | Development of diagnostic... +3 projectsNIH| OST DOCTORAL TRAINING IN EMOTION RESEARCH ,SSHRC ,UKRI| Development of diagnostic device to differentiate between bipolar and unipolar depression ,ARC| Discovery Projects - Grant ID: DP180102384 ,UKRI| A Smart System to Empower Healthy Food Choices ,EC| JITSUVAXBuchanan, Erin M.; Lewis, Savannah C.; Paris, Bastien; Forscher, Patrick S.; Pavlacic, Jeffrey M.; Beshears, Julie E.; Drexler, Shira Meir; Gourdon-Kanhukamwe, Amélie; Mallik, Peter R.; Silan, Miguel Alejandro A.; Miller, Jeremy K.; IJzerman, Hans; Moshontz, Hannah; Beaudry, Jennifer L.; Suchow, Jordan W.; Chartier, Christopher R.; Coles, Nicholas A.; Sharifian, Mohammad Hasan; Todsen, Anna Louise; Levitan, Carmel A.; Azevedo, Flávio; Legate, Nicole; Heller, Blake; Rothman, Alexander J.; Dorison, Charles A.; Gill, Brian P.; Wang, Ke; Rees, Vaughan W.; Gibbs, Nancy; Goldenberg, Amit; Thi Nguyen, Thuy vy; Gross, James J.; Kaminski, Gwenaêl; von Bastian, Claudia C.; Paruzel-Czachura, Mariola; Mosannenzadeh, Farnaz; Azouaghe, Soufian; Bran, Alexandre; Ruiz-Fernandez, Susana; Santos, Anabela Caetano; Reggev, Niv; Zickfeld, Janis H.; Akkas, Handan; Pantazi, Myrto; Ropovik, Ivan; Korbmacher, Max; Arriaga, Patrícia; Gjoneska, Biljana; Warmelink, Lara; Alves, Sara G.; de Holanda Coelho, Gabriel Lins; Stieger, Stefan; Schei, Vidar; Hanel, Paul H.P.; Szaszi, Barnabas; Fedotov, Maksim; Antfolk, Jan; Marcu, Gabriela Mariana; Schrötter, Jana; Kunst, Jonas R.; Geiger, Sandra J.; Adetula, Adeyemi; Kocalar, Halil Emre; Kielińska, Julita; Kačmár, Pavol; Bokkour, Ahmed; Galindo-Caballero, Oscar J.; Djamai, Ikhlas; Pöntinen, Sara Johanna; Agesin, Bamikole Emmanuel; Jernsäther, Teodor; Urooj, Anum; Rachev, Nikolay R.; Koptjevskaja-Tamm, Maria; Kurfalı, Murathan; Pit, Ilse L.; Li, Ranran; Çoksan, Sami; Dubrov, Dmitrii; Paltrow, Tamar Elise; Baník, Gabriel; Korobova, Tatiana; Studzinska, Anna; Jiang, Xiaoming; Aruta, John Jamir Benzon R.; Vintr, Jáchym; Chiu, Faith; Kaliska, Lada; Berkessel, Jana B.; Tümer, Murat; Morales-Izquierdo, Sara; Chuan-Peng, Hu; Vezirian, Kevin; Rosa, Anna Dalla; Bialobrzeska, Olga; Vasilev, Martin R.; Beitner, Julia; Kácha, Ondřej; Žuro, Barbara; Westerlund, Minja; Nedelcheva-Datsova, Mina; Findor, Andrej; Krupić, Dajana; Kowal, Marta; Askelund, Adrian Dahl; Pourafshari, Razieh; Đorđević, Jasna Milošević; Schmidt, Nadya Daniela; Baklanova, Ekaterina; Szala, Anna; Zakharov, Ilya; Vranka, Marek A.; Ihaya, Keiko; Grano, Caterina; Cellini, Nicola; Białek, Michał; Anton-Boicuk, Lisa; Dalgar, Ilker; Adıgüzel, Arca; Verharen, Jeroen P.H.; Maturan, Princess Lovella G.; Kassianos, Angelos P.; Oliveira, Raquel; Čadek, Martin; Adoric, Vera Cubela; Özdoğru, Asil Ali; Sverdrup, Therese E.; Aczel, Balazs; Zambrano, Danilo; Ahmed, Afroja; Tamnes, Christian K.; Yamada, Yuki; Volz, Leonhard; Sunami, Naoyuki; Suter, Lilian; Vieira, Luc; Groyecka-Bernard, Agata; Kamburidis, Julia Arhondis; Reips, Ulf Dietrich; Harutyunyan, Mikayel; Adetula, Gabriel Agboola; Allred, Tara Bulut; Barzykowski, Krystian; Antazo, Benedict G.; Zsido, Andras N.; Šakan, Dušana Dušan; Cyrus-Lai, Wilson; Ahlgren, Lina Pernilla; Hruška, Matej; Vega, Diego; Manunta, Efisio; Mokady, Aviv; Capizzi, Mariagrazia; Martončik, Marcel; Say, Nicolas; Filip, Katarzyna; Vilar, Roosevelt; Staniaszek, Karolina; Vdovic, Milica; Adamkovic, Matus; Johannes, Niklas; Hajdu, Nandor; Cohen, Noga; Overkott, Clara; Krupić, Dino; Hubena, Barbora; Nilsonne, Gustav; Mioni, Giovanna; Solorzano, Claudio Singh; Ishii, Tatsunori; Chen, Zhang; Kushnir, Elizaveta; Karaarslan, Cemre; Ribeiro, Rafael R.; Khaoudi, Ahmed; Kossowska, Małgorzata; Bavolar, Jozef; Hoyer, Karlijn; Roczniewska, Marta; Karababa, Alper; Becker, Maja; Monteiro, Renan P.; Kunisato, Yoshihiko; Metin-Orta, Irem; Adamus, Sylwia; Kozma, Luca; Czarnek, Gabriela; Domurat, Artur; Štrukelj, Eva; Alvarez, Daniela Serrato; Parzuchowski, Michal; Massoni, Sébastien; Czamanski-Cohen, Johanna; Pronizius, Ekaterina; Muchembled, Fany; van Schie, Kevin; Saçaklı, Aslı; Hristova, Evgeniya; Kuzminska, Anna O.; Charyate, Abdelilah; Musser, Erica D.; Sirota, Miroslav; Ross, Robert M.; Foroni, Francesco; Almeida, Inês A.T.; Grigoryev, Dmitry; Lewis, David M.G.; Holford, Dawn L.; Janssen, Steve M.J.; Tatachari, Srinivasan; Batres, Carlota; Olofsson, Jonas K.; Belaus, Anabel; Pfuhl, Gerit; Corral-Frias, Nadia Sarai; Sousa, Daniela; Voracek, Martin; DeBruine, Lisa M.; Anne, Michele; Očovaj, Sanja Batić; Arvanitis, Alexios; Arinze, Nwadiogo Chisom; Bundt, Carsten; Lamm, Claus; Calin-Jageman, Robert J.; Karekla, Maria; Hricova, Monika; Koehn, Monica A.; Bai, Hui; Krafnick, Anthony J.; Lins, Samuel; Macapagal, Paulo Manuel L.; Szwed, Paulina; Zdybek, Przemysław Marcin; Tran, Ulrich S.; Albayrak-Aydemir, Nihan; Dixson, Barnaby James Wyld; Jaeger, Bastian; Butt, Muhammad Mussaffa; Sorokowska, Agnieszka; Willis, Megan L.; Stephen, Ian D.; de la Rosa-Gómez, Anabel; Sutherland, Clare A.M.; Behzadnia, Behzad; Ogbonnaya, Chisom Esther; Fu, Cynthia H.Y.; Rahal, Rima Maria; Hostler, Thomas J.; Khosla, Meetu; Lazarevic, Ljiljana B.; Luis, Elkin O.; Reeck, Crystal; Ryan, Richard M.; Travaglino, Giovanni A.; Chopik, William J.; Xiao, Qinyu; Verbruggen, Frederick;handle: 11250/3084711 , 20.500.12809/10543 , 2066/290924 , 20.500.11820/fd77e6a0-c291-42bc-9eb4-3c8be177815b , 1871.1/493d9e6f-23c0-408c-b085-5fb867ea7059 , 10216/148131 , 20.500.14178/2132 , 10451/56312 , 10071/28653 , 21.11116/0000-000D-FCE3-7 , 21.11116/0000-000D-FCE5-5 , 20.500.14178/2122 , 1854/LU-01HM8BT6M0E6FH11H697ZJCYD2
pmid: 36774440
pmc: PMC9918828
handle: 11250/3084711 , 20.500.12809/10543 , 2066/290924 , 20.500.11820/fd77e6a0-c291-42bc-9eb4-3c8be177815b , 1871.1/493d9e6f-23c0-408c-b085-5fb867ea7059 , 10216/148131 , 20.500.14178/2132 , 10451/56312 , 10071/28653 , 21.11116/0000-000D-FCE3-7 , 21.11116/0000-000D-FCE5-5 , 20.500.14178/2122 , 1854/LU-01HM8BT6M0E6FH11H697ZJCYD2
pmid: 36774440
pmc: PMC9918828
In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data. Funder: Horizon 2020 grant 964728 (JITSUVAX) from the European Commission and was supported by a United Kingdom Research and Innovation (UKRI) Research Fellowship grant ES/V011901/1 Funder: Program FUTURE LEADER of Lorraine Université d’Excellence within the program Investissements Avenir (ANR-15-IDEX-04-LUE) operated by the French National Research Agency Funder: Association Nationale de la Recherche et de la Technologie (National Association for Research and Technology); doi: https://doi.org/10.13039/501100003032 Funder: The work of Dmitrii Dubrov was supported within the framework of the Basic Research Program at HSE University, RF Funder: Rubicon grant (019.183SG.007) from the Netherlands Organization for Scientific Research (NWO) Funder: Agentúra na podporu výskumu a vývoja (Slovak Research and Development Agency) - APVV-17-0596 Funder: UID/PSI/03125/2019 from the Portuguese National Foundation for Science and Technology (FCT). Funder: Kingston University (Kingston University, London); doi: https://doi.org/10.13039/100010049 Funder: Association Nationale de la Recherche Scientifique and Pacifica (CIFRE grant 2017/0245) Funder: Statutory funds of the Institute of Psychology, University of Wroclaw Funder: PSA research grant ($285.59) for the PSACR projects data collection Funder: The Japan Society for the Promotion of Science KAKENHI [19K14370] Funder: Social Science and Humanities Research Council of Canada Funder: National Science Centre, Poland (2019/35/B/HS6/00528) Funder: Slovak Research and Development Agency - APVV-17-0596 Funder: The Institute of Psychology, Jagiellonian University Funder: JSPS KAKENHI Grant Numbers JP18K12015 and JP20H04581 Funder: University of Desarrollo, Faculty of Psychology Funder: IDN Being Human Lab (University of Wrocław) Funder: Dominican University Faculty Support Grant Funder: Vicerrectoria de Investigaciones, Uniandes Funder: Australian Research Council (DP180102384) Funder: Amazon Web Services (AWS) Imagine Grant Funder: HSE University Basic Research Program Funder: Progres Q18, Charles University Funder: ANID - Fondecyt 1201513 Funder: Huo Family Foundation Funder: PRIMUS/20/HUM/009 Funder: FONDECYT 1221538
NARCIS arrow_drop_down CU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMuğla Sıtkı Koçman Üniversitesi Kurumsal Akademik Arşiv SistemiConference object . 2023Ghent University Academic BibliographyArticle . 2023Data sources: Ghent University Academic BibliographyJyväskylä University Digital ArchiveArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Jyväskylä University Digital ArchiveUniversidade de Lisboa: Repositório.ULOther literature type . 2023License: CC BYData sources: Universidade de Lisboa: Repositório.ULRepositório Aberto da Universidade do PortoArticle . 2023Data sources: Repositório Aberto da Universidade do PortoCU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMémoires en Sciences de l'Information et de la CommunicationArticle . 2023Full-Text: https://hal.science/hal-04294810/documentHAL Paris Nanterre; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41597-022-01811-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!visibility 181visibility views 181 download downloads 123 Powered bymore_vert NARCIS arrow_drop_down CU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMuğla Sıtkı Koçman Üniversitesi Kurumsal Akademik Arşiv SistemiConference object . 2023Ghent University Academic BibliographyArticle . 2023Data sources: Ghent University Academic BibliographyJyväskylä University Digital ArchiveArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Jyväskylä University Digital ArchiveUniversidade de Lisboa: Repositório.ULOther literature type . 2023License: CC BYData sources: Universidade de Lisboa: Repositório.ULRepositório Aberto da Universidade do PortoArticle . 2023Data sources: Repositório Aberto da Universidade do PortoCU Research Publications RepositoryArticle . 2023License: CC BYData sources: CU Research Publications RepositoryMémoires en Sciences de l'Information et de la CommunicationArticle . 2023Full-Text: https://hal.science/hal-04294810/documentHAL Paris Nanterre; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1038/s41597-022-01811-7&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint 2023Embargo end date: 01 Jan 2023Publisher:arXiv Funded by:EC | DUSTEC| DUSTAuthors: Oswald, Yannick; Malleson, Nicolas; Suchak, Keiran;Oswald, Yannick; Malleson, Nicolas; Suchak, Keiran;Global problems, such as pandemics and climate change, require rapid international coordination and diffusion of policy. These phenomena are rare however, with one notable example being the international policy response to the COVID-19 pandemic in early 2020. Here we build an agent-based model of this rapid policy diffusion, where countries constitute the agents and with the principal mechanism for diffusion being peer mimicry. Since it is challenging to predict accurately the policy diffusion curve, we utilize data assimilation, that is an ``on-line'' feed of data to constrain the model against observations. The specific data assimilation algorithm we apply is a particle filter because of its convenient implementation, its ability to handle categorical variables and because the model is not overly computationally expensive, hence a more efficient algorithm is not required. We find that the model alone is able to predict the policy diffusion relatively well with an ensemble of at least 100 simulation runs. The particle filter however improves the fit to the data, reliably so from 500 runs upwards, and increasing filtering frequency results in improved prediction.
ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.48550/arxiv.2302.11277&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 40visibility views 40 download downloads 30 Powered bymore_vert ZENODO arrow_drop_down https://doi.org/10.48550/arxiv...Article . 2023License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.48550/arxiv.2302.11277&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu