Michael Achmann-Denkler
2024
Divergent Discourses: A Comparative Examination of Blackout Tuesday and #BlackLivesMatter on Instagram
Aenne Knierim
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Michael Achmann-Denkler
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Ulrich Heid
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Christian Wolff
Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)
On May 25th, 2020, a viral eleven-minute clip showing the murder of George Floyd sparked international outrage and solidarity, leading to the digital memorial event Blackout Tuesday on Instagram. We analyzed posts to compare Blackout Tuesday discourse with #blacklivesmatter movement conversations. Using topic modeling, we identified dominant themes and counter-narratives in Blackout Tuesday and #blacklivesmatter captions. Using hashtag co-occurrence analysis, we investigatehashtag networks to situate the discourses within spheres of Instagram activism. Our findings indicate that both corpora share themes like “calls to action”, but Blackout Tuesday posts are shorter and solidarity-focused, while #blacklivesmatter posts are longer and address white privilege more explicitly. #blacklivesmatter is linked to anti-racist activism hashtags, while Blackout Tuesday connects more with popular culture and #Alllivesmatter. This supports qualitative research on Blackout Tuesday’s performative allyship, adding a quantitative perspective to the field.
Detecting Calls to Action in Multimodal Content: Analysis of the 2021 German Federal Election Campaign on Instagram
Michael Achmann-Denkler
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Jakob Fehle
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Mario Haim
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Christian Wolff
Proceedings of the 4th Workshop on Computational Linguistics for the Political and Social Sciences: Long and short papers
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.