Actantial Networks

Data Skeptic · Beginner ·🛡️ AI Safety & Ethics ·1y ago

Key Takeaways

Actantial Networks, a graph-based representation of narratives, is presented by Armin Pournaki, utilizing natural language processing and network science to analyze political narratives and expose conflicting narratives around events like COVID-19, climate change, and the war in Ukraine.

Original Description

In this episode, listeners will learn about Actantial Networks—graph-based representations of narratives where nodes are actors (such as people, institutions, or abstract entities) and edges represent the actions or relationships between them. The one who will present these networks is our guest Armin Pournaki, a joint PhD candidate at the Max Planck Institute and Sciences, who specializes in computational social science, where he develops methods to extract and analyze political narratives using natural language processing and network science. Armin explains how these methods can expose conflicting narratives around the same events, as seen in debates on COVID-19, climate change, or the war in Ukraine. Listeners will also discover how this approach helps make large-scale discourse—from millions of tweets or political speeches—more transparent and interpretable, offering tools for studying polarization, issue alignment, and narrative-driven persuasion in digital societies. Follow our guest Armin Pournaki's Webpage Twitter/X Bluesky Papers in focus How influencers and multipliers drive polarization and issue alignment on Twitter/X, 2025 A graph-based approach to extracting narrative signals from public discourse, 2024
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Actantial Networks is a graph-based approach to represent and analyze narratives, helping to expose conflicting narratives and make large-scale discourse more transparent and interpretable. This approach has applications in studying polarization, issue alignment, and narrative-driven persuasion in digital societies. By utilizing natural language processing and network science, listeners can develop methods to extract and analyze political narratives.

Key Takeaways
  1. Define Actantial Networks and their components
  2. Understand how to apply natural language processing and network science to analyze narratives
  3. Develop methods to extract narrative signals from public discourse
  4. Analyze conflicting narratives around events like COVID-19, climate change, and the war in Ukraine
  5. Study polarization and issue alignment in digital societies
💡 Actantial Networks can help expose conflicting narratives and make large-scale discourse more transparent and interpretable, offering tools for studying polarization, issue alignment, and narrative-driven persuasion in digital societies.

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