Hartwig, Katrin ; Reuter, Christian (2022)
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter.
14. Internationale Tagung Wirtschaftsinformatik (WI 2019). Siegen, Germany (23.-27.2.2019)
doi: 10.26083/tuprints-00020747
Konferenzveröffentlichung, Zweitveröffentlichung, Verlagsversion
Kurzbeschreibung (Abstract)
The importance of dealing withfake newsonsocial mediahas increased both in political and social contexts.While existing studies focus mainly on how to detect and label fake news, approaches to assist usersin making their own assessments are largely missing. This article presents a study on how Twitter-users’assessmentscan be supported by an indicator-based white-box approach.First, we gathered potential indicators for fake news that have proven to be promising in previous studies and that fit our idea of awhite-box approach. Based on those indicators we then designed and implemented the browser-plugin TrusyTweet, which assists users on Twitterin assessing tweetsby showing politically neutral and intuitive warnings without creating reactance. Finally, we suggest the findings of our evaluations with a total of 27 participants which lead to further design implicationsfor approachesto assistusers in dealing with fake news.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Hartwig, Katrin ; Reuter, Christian |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Ort: | Darmstadt |
| Verlag: | Association for Information Systems AIS |
| Buchtitel: | Tagungsband WI 2019 : Human Practice. Digital Ecologies. Our Future. |
| Veranstaltungstitel: | 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) |
| Veranstaltungsort: | Siegen, Germany |
| Veranstaltungsdatum: | 23.-27.2.2019 |
| DOI: | 10.26083/tuprints-00020747 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/20747 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichungsservice |
| Kurzbeschreibung (Abstract): | The importance of dealing withfake newsonsocial mediahas increased both in political and social contexts.While existing studies focus mainly on how to detect and label fake news, approaches to assist usersin making their own assessments are largely missing. This article presents a study on how Twitter-users’assessmentscan be supported by an indicator-based white-box approach.First, we gathered potential indicators for fake news that have proven to be promising in previous studies and that fit our idea of awhite-box approach. Based on those indicators we then designed and implemented the browser-plugin TrusyTweet, which assists users on Twitterin assessing tweetsby showing politically neutral and intuitive warnings without creating reactance. Finally, we suggest the findings of our evaluations with a total of 27 participants which lead to further design implicationsfor approachesto assistusers in dealing with fake news. |
| Freie Schlagworte: | Fake News, Social Media, Twitter, Plugin |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-207476 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik 300 Sozialwissenschaften > 380 Handel, Kommunikation, Verkehr |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Wissenschaft und Technik für Frieden und Sicherheit (PEASEC) Profilbereiche Profilbereiche > Cybersicherheit (CYSEC) LOEWE LOEWE > LOEWE-Zentren LOEWE > LOEWE-Zentren > CRISP - Center for Research in Security and Privacy Zentrale Einrichtungen Zentrale Einrichtungen > Interdisziplinäre Arbeitsgruppe Naturwissenschaft, Technik und Sicherheit (IANUS) |
| Hinterlegungsdatum: | 15 Dez 2022 12:42 |
| Letzte Änderung: | 02 Jan 2023 09:13 |
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| Zugehörige Links: | |
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