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Detecting Calls to Action in Multimodal Content: Analysis of the 2021 German Federal Election Campaign on Instagram
Achmann-Denkler, Michael
, Fehle, Jakob, Haim, Mario und Wolff, Christian
(2024)
Detecting Calls to Action in Multimodal Content: Analysis of the 2021 German Federal Election Campaign on Instagram.
arXiv, 2409.02690.
Veröffentlichungsdatum dieses Volltextes: 22 Okt 2024 09:21
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.59409
Zusammenfassung
This study investigates the automated classification of Calls to Action (CTAs) within the 2021 German Instagram election campaign to advance the understanding of mobilization in social media contexts. We analyzed over 2,208 Instagram stories and 712 posts using fine-tuned BERT models and OpenAI's GPT-4 models. The fine-tuned BERT model incorporating synthetic training data achieved a macro F1 ...
This study investigates the automated classification of Calls to Action (CTAs) within the 2021 German Instagram election campaign to advance the understanding of mobilization in social media contexts. We analyzed over 2,208 Instagram stories and 712 posts using fine-tuned BERT models and OpenAI's GPT-4 models. The fine-tuned BERT model incorporating synthetic training data achieved a macro F1 score of 0.93, demonstrating a robust classification performance. Our analysis revealed that 49.58% of Instagram posts and 10.64% of stories contained CTAs, highlighting significant differences in mobilization strategies between these content types. Additionally, we found that FDP and the Greens had the highest prevalence of CTAs in posts, whereas CDU and CSU led in story CTAs.
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| Dokumentenart | Artikel | ||||||
| Titel eines Journals oder einer Zeitschrift | arXiv | ||||||
| Seitenbereich: | 2409.02690 | ||||||
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| Datum | 4 September 2024 | ||||||
| Institutionen | Sprach- und Literatur- und Kulturwissenschaften > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff) Informatik und Data Science > Fachbereich Menschzentrierte Informatik > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff) | ||||||
| Identifikationsnummer |
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| Stichwörter / Keywords | Social and Information Networks, Computation and Language | ||||||
| Dewey-Dezimal-Klassifikation | 000 Informatik, Informationswissenschaft, allgemeine Werke > 004 Informatik | ||||||
| Status | Veröffentlicht | ||||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||||
| An der Universität Regensburg entstanden | Ja | ||||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-594098 | ||||||
| Dokumenten-ID | 59409 |
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