EPJ Data Science最新文献

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Detecting coordinated and bot-like behavior in Twitter: the Jürgen Conings case 检测 Twitter 中的协调行为和机器人行为:Jürgen Conings 案例
EPJ Data Science Pub Date : 2024-06-05 DOI: 10.1140/epjds/s13688-024-00477-y
Bart De Clerck, J. C. Fernández Toledano, Filip Van Utterbeeck, Luis E. C. Rocha
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引用次数: 0
Online disinformation in the 2020 U.S. election: swing vs. safe states 2020 年美国大选中的网络虚假信息:摇摆州与安全州
EPJ Data Science Pub Date : 2024-02-28 DOI: 10.48550/arXiv.2402.18664
Manuel Pratelli, M. Petrocchi, F. Saracco, R. Nicola
{"title":"Online disinformation in the 2020 U.S. election: swing vs. safe states","authors":"Manuel Pratelli, M. Petrocchi, F. Saracco, R. Nicola","doi":"10.48550/arXiv.2402.18664","DOIUrl":"https://doi.org/10.48550/arXiv.2402.18664","url":null,"abstract":"For U.S. presidential elections, most states use the so-called winner-take-all system, in which the state’s presidential electors are awarded to the winning political party in the state after a popular vote phase, regardless of the actual margin of victory. Therefore, election campaigns are especially intense in states where there is no clear direction on which party will be the winning party. These states are often referred to as swing states . To measure the impact of such an election law on the campaigns, we analyze the Twitter activity surrounding the 2020 US preelection debate, with a particular focus on the spread of disinformation. We find that about 88% of the online traffic was associated with swing states. In addition, the sharing of links to unreliable news sources is significantly more prevalent in tweets associated with swing states: in this case, untrustworthy tweets are predominantly generated by automated accounts. Furthermore, we observe that the debate is mostly led by two main communities, one with a predominantly Republican affiliation and the other with accounts of different political orientations. Most of the disinformation comes from the former.","PeriodicalId":507700,"journal":{"name":"EPJ Data Science","volume":"23 3","pages":"1-23"},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140420316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptation of student behavioural routines during Covid-19: a multimodal approach 在 Covid-19 期间调整学生行为常规:一种多模式方法
EPJ Data Science Pub Date : 2023-06-14 DOI: 10.1140/epjds/s13688-023-00429-y
Nicolo A. Girardini, Simone Centellegher, Andrea Passerini, Ivano Bison, Fausto Giunchiglia, B. Lepri
{"title":"Adaptation of student behavioural routines during Covid-19: a multimodal approach","authors":"Nicolo A. Girardini, Simone Centellegher, Andrea Passerini, Ivano Bison, Fausto Giunchiglia, B. Lepri","doi":"10.1140/epjds/s13688-023-00429-y","DOIUrl":"https://doi.org/10.1140/epjds/s13688-023-00429-y","url":null,"abstract":"","PeriodicalId":507700,"journal":{"name":"EPJ Data Science","volume":"40 1","pages":"1-22"},"PeriodicalIF":0.0,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139370016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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