Hartwig, Katrin ; Schmid, Stefka ; Biselli, Tom ; Pleil, Helene ; Reuter, Christian (2024)
Misleading Information in Crises: Exploring Content-specific Indicators on Twitter from a User Perspective.
In: Behaviour & Information Technology, 2024
doi: 10.1080/0144929X.2024.2373166
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Recent crises like the COVID-19 pandemic provoked an increasing appearance of misleading information, emphasizing the need for effective user-centered countermeasures as an important field in HCI research. This work investigates how content-specific user-centered indicators can contribute to an informed approach to misleading information. In a threefold study, we conducted an in-depth content analysis of 2,382 German tweets on Twitter (now X) to identify topical (e.g., 5G), formal (e.g., links), and rhetorical (e.g., sarcasm) characteristics through manual coding, followed by a qualitative online survey to evaluate which indicators users already use autonomously to assess a tweet’s credibility. Subsequently, in a think-aloud study participants qualitatively evaluated the identified indicators in terms of perceived comprehensibility and usefulness. While a number of indicators were found to be particularly comprehensible and useful (e.g., claim for absolute truth and rhetorical questions), our findings reveal limitations of indicator-based interventions, particularly for people with entrenched conspiracy theory views. We derive four implications for digitally supporting users in dealing with misleading information, especially during crises.
Typ des Eintrags: | Artikel |
---|---|
Erschienen: | 2024 |
Autor(en): | Hartwig, Katrin ; Schmid, Stefka ; Biselli, Tom ; Pleil, Helene ; Reuter, Christian |
Art des Eintrags: | Bibliographie |
Titel: | Misleading Information in Crises: Exploring Content-specific Indicators on Twitter from a User Perspective |
Sprache: | Deutsch |
Publikationsjahr: | 8 Juli 2024 |
Verlag: | Taylor & Francis |
Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Behaviour & Information Technology |
Jahrgang/Volume einer Zeitschrift: | 2024 |
Kollation: | 34 Seiten |
DOI: | 10.1080/0144929X.2024.2373166 |
Kurzbeschreibung (Abstract): | Recent crises like the COVID-19 pandemic provoked an increasing appearance of misleading information, emphasizing the need for effective user-centered countermeasures as an important field in HCI research. This work investigates how content-specific user-centered indicators can contribute to an informed approach to misleading information. In a threefold study, we conducted an in-depth content analysis of 2,382 German tweets on Twitter (now X) to identify topical (e.g., 5G), formal (e.g., links), and rhetorical (e.g., sarcasm) characteristics through manual coding, followed by a qualitative online survey to evaluate which indicators users already use autonomously to assess a tweet’s credibility. Subsequently, in a think-aloud study participants qualitatively evaluated the identified indicators in terms of perceived comprehensibility and usefulness. While a number of indicators were found to be particularly comprehensible and useful (e.g., claim for absolute truth and rhetorical questions), our findings reveal limitations of indicator-based interventions, particularly for people with entrenched conspiracy theory views. We derive four implications for digitally supporting users in dealing with misleading information, especially during crises. |
Freie Schlagworte: | Crisis, HCI, Projekt-NEBULA, A-Paper, Ranking-CORE-A, Ranking-ImpactFactor, Projekt-ATHENE-PriVis |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Wissenschaft und Technik für Frieden und Sicherheit (PEASEC) Forschungsfelder Forschungsfelder > Information and Intelligence Forschungsfelder > Information and Intelligence > Cybersecurity & Privacy |
Hinterlegungsdatum: | 23 Jan 2025 08:35 |
Letzte Änderung: | 23 Jan 2025 08:35 |
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