Online-Ressource | |
Verfasst von: | Berg, Esther van den [VerfasserIn] |
Korfhage, Katharina [VerfasserIn] | |
Ruppenhofer, Josef [VerfasserIn] | |
Wiegand, Michael [VerfasserIn] | |
Markert, Katja [VerfasserIn] | |
Titel: | Doctor Who? |
Titelzusatz: | Framing through names and titles in German |
Verf.angabe: | Esther van den Berg, Katharina Korfhage, Josef Ruppenhofer, Michael Wiegand and Katja Markert |
Jahr: | 2020 |
Umfang: | 9 S. |
Fussnoten: | Gesehen am 05.01.2021 |
Titel Quelle: | Enthalten in: International Conference on Language Resources and Evaluation (12. : 2020 : Marseille)LREC 2020 Marseille |
Ort Quelle: | Paris : The European Language Resources Association (ELRA), 2020 |
Jahr Quelle: | 2020 |
Band/Heft Quelle: | (2020), Seite 4924-4932 |
ISBN Quelle: | 9791095546344 |
Abstract: | Entity framing is the selection of aspects of an entity to promote a particular viewpoint towards that entity. We investigate entity framing of political figures through the use of names and titles in German online discourse, enhancing current research in entity framing through titling and naming that concentrates on English only. We collect tweets that mention prominent German politicians and annotate them for stance. We find that the formality of naming in these tweets correlates positively with their stance. This confirms sociolinguistic observations that naming and titling can have a status-indicating function and suggests that this function is dominant in German tweets mentioning political figures. We also find that this status-indicating function is much weaker in tweets from users that are politically left-leaning than in tweets by right-leaning users. This is in line with observations from moral psychology that left-leaning and right-leaning users assign different importance to maintaining social hierarchies. |
URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt. Volltext: https://www.aclweb.org/anthology/2020.lrec-1.606 |
Datenträger: | Online-Ressource |
Sprache: | eng |
Bibliogr. Hinweis: | Forschungsdaten: Berg, Esther van den: German Twitter Titling Corpus |
K10plus-PPN: | 1743900244 |
Verknüpfungen: | → Sammelwerk |