分析2021年德国大选期间Instagram的动员话术，发现不同政党在帖文和故事中策略不同。
Detecting Calls to Action in Multimodal Content: Analysis of the 2021 German Federal Election Campaign on Instagram
- 用微调BERT+合成数据实现93%的准确率，自动识别动员口号。
- 近半数帖文含动员话术，但故事中仅约10%有，显示内容形式差异。
- 绿党和自由民主党在帖文中动员最多，基民盟与基社盟则在故事中领先。
本研究探讨了在2021年德国联邦选举期间，利用自动化方法对Instagram内容中的行动号召（CTAs）进行分类，以增进对社交媒体动员机制的理解。我们分析了超过2,208条Instagram Stories和712篇帖子，采用微调后的BERT模型及OpenAI的GPT-4模型。通过引入合成训练数据，微调后的BERT模型达到了0.93的宏平均F1分数，表现出色。分析发现，49.58%的帖子包含CTA，而故事中仅有10.64%包含，凸显两类内容在动员策略上的显著差异。此外，绿党与自由民主党（FDP）在帖子中使用最多的行动号召，而基民盟（CDU）与基社盟（CSU）在故事中占比最高。
原文摘要 · Abstract (English)
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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