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Misleading Information in Crises: Exploring Content-specific Indicators on Twitter from a User Perspective

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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