El Baff, Roxanne und Al Khatib, Khalid und Stein, Benno und Wachsmuth, Henning (2020) Persuasiveness of News Editorials depending on Ideology and Personality. In: Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media, 3, Seiten 29-40. Association for Computational Linguistics, Barcelona, Spain (Online). Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media, 2020-12-13, Barcelona (Online).
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Offizielle URL: https://www.aclweb.org/anthology/2020.peoples-1.4
Kurzfassung
News editorials aim to shape the opinions of their readership and the general public on timely controversial issues. The impact of an editorial on the reader’s opinion does not only depend on its content and style, but also on the reader’s profile. Previous work has studied the effect of editorial style depending on general political ideologies (liberals vs.conservatives). In our work, we dig deeper into the persuasiveness of both content and style, exploring the role of the intensity of an ideology (lean vs.extreme) and the reader’s personality traits (agreeableness, conscientiousness, extraversion, neuroticism, and openness). Concretely, we train content- and style-based models on New York Times editorials for different ideology- and personality-specific groups. Our results suggest that particularly readers with extreme ideology and non ‘‘role model” personalities are impacted by style. We further analyze the importance of various text features with respect to the editorials’ impact, the readers’ profile, and the editorials’ geographical scope.
elib-URL des Eintrags: | https://elib.dlr.de/140158/ | ||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Programmrede) | ||||||||||||||||||||
Titel: | Persuasiveness of News Editorials depending on Ideology and Personality | ||||||||||||||||||||
Autoren: |
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Datum: | Dezember 2020 | ||||||||||||||||||||
Erschienen in: | Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||
Band: | 3 | ||||||||||||||||||||
Seitenbereich: | Seiten 29-40 | ||||||||||||||||||||
Verlag: | Association for Computational Linguistics | ||||||||||||||||||||
Name der Reihe: | Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | natural language processing, discourse analysis, computational social science, style analysis | ||||||||||||||||||||
Veranstaltungstitel: | Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media | ||||||||||||||||||||
Veranstaltungsort: | Barcelona (Online) | ||||||||||||||||||||
Veranstaltungsart: | Workshop | ||||||||||||||||||||
Veranstaltungsdatum: | 13 Dezember 2020 | ||||||||||||||||||||
Veranstalter : | Malvina Nissim, University of Groningen - Viviana Patti, University of Turin - Barbara Plank, IT University of Copenhagen | ||||||||||||||||||||
HGF - Forschungsbereich: | keine Zuordnung | ||||||||||||||||||||
HGF - Programm: | keine Zuordnung | ||||||||||||||||||||
HGF - Programmthema: | keine Zuordnung | ||||||||||||||||||||
DLR - Schwerpunkt: | keine Zuordnung | ||||||||||||||||||||
DLR - Forschungsgebiet: | keine Zuordnung | ||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | keine Zuordnung | ||||||||||||||||||||
Standort: | Oberpfaffenhofen | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Softwaretechnologie Institut für Softwaretechnologie > Intelligente und verteilte Systeme | ||||||||||||||||||||
Hinterlegt von: | El Baff, Roxanne | ||||||||||||||||||||
Hinterlegt am: | 11 Jan 2021 14:15 | ||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:41 |
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