System identifies opposing political stories in social media tweets
Automated Identification of Competing Narratives in Political Discourse on Social Media
Computation and LanguageSocial and Information Networks
Summary
Social media is full of different stories and opinions about politics, and sometimes these stories compete with each other. The authors created a way for computers to automatically find these competing stories by looking at tweets from German politicians. They use smart language tools to group tweets into events and link them into stories, showing how different groups talk about the same issues in different ways. This helps people understand how political conversations happen online and how different viewpoints spread.
What this means in practice
- •For social media platform teams: Track and flag conflicting political narratives spreading on social media to improve content moderation strategies.
- •For political campaign teams: Monitor trending topics to understand and respond to rival narratives shaping voter opinions in real time.
Authors
Sergej Wildemann, Erick Elejalde
Abstract
Social media platforms have become central to shaping political discourse, serving as arenas where narratives form and evolve, influencing public opinion. Identifying and analyzing these narratives, particularly when they compete across different political ideologies, is crucial for understanding the dynamics of modern political communication. This paper presents an unsupervised framework for identifying and characterizing competing narratives in political discourse on social media, focusing on German politicians' tweets. The framework employs a multi-stage pipeline that integrates natural language processing techniques such as topic modeling, event detection, and event linking. By forming data into coherent stories and uncovering the distinct perspectives of user communities, the system is able to detect the key competing narratives, highlighting the divergent framings and conflicts surrounding trending political topics. Two case studies on polarizing political issues demonstrate the efficacy of the methodology, showcasing its ability to uncover and analyze divergent viewpoints. The findings contribute to the broader understanding of how narratives propagate within the digital public sphere and offer insights for policymakers, social media platforms, and researchers interested in monitoring political discourse.