# Detecting Calls to Action in Multimodal Content: Analysis of the 2021 German Federal Election Campaign on Instagram

arXiv: https://arxiv.org/abs/2409.02690 · HTML: https://mlsanity.com/paper/2409.02690/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 40 references that are in the map.
- First posted on arXiv 4 Sep 2024.

## Builds on (most cited first, 7 of 7)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks](https://mlsanity.com/paper/2303.15056/) (2023)
- [Automatic Prompt Optimization with "Gradient Descent" and Beam Search](https://mlsanity.com/paper/2305.03495/) (2023)
- [German's Next Language Model](https://mlsanity.com/paper/2010.10906/) (2020)
- [Best Practices for Text Annotation with Large Language Models](https://mlsanity.com/paper/2402.05129/) (2024)
- [Exploiting the relationship between visual and textual features in social networks for image classification with zero-shot deep learning](https://mlsanity.com/paper/2107.03751/) (2021)

## Built on by (most cited first, 2 of 2)

- [From Measurement Instruments to Data: Leveraging Theory-Driven Synthetic Training Data for Classifying Social Constructs](https://mlsanity.com/paper/2410.12622/) (2024)
- [Seeing Candidates at Scale: Multimodal LLMs for Visual Political Communication on Instagram](https://mlsanity.com/paper/2604.19489/) (2026)

## Abstract (arXiv)

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.