InfoPattern: Unveiling Information Propagation Patterns in Social Media
This addresses the challenge of analyzing information propagation for researchers and policymakers, but it appears incremental as it combines existing techniques like red teaming and stance detection into a unified tool.
The paper tackles the problem of understanding how information spreads in social media by developing InfoPattern, a demo that simulates adversary responses, detects political stances, and reveals propagation patterns across ideological communities, with a live demo and code provided.
Social media play a significant role in shaping public opinion and influencing ideological communities through information propagation. Our demo InfoPattern centers on the interplay between language and human ideology. The demo (Code: https://github.com/blender-nlp/InfoPattern ) is capable of: (1) red teaming to simulate adversary responses from opposite ideology communities; (2) stance detection to identify the underlying political sentiments in each message; (3) information propagation graph discovery to reveal the evolution of claims across various communities over time. (Live Demo: https://incas.csl.illinois.edu/blender/About )