Identification and characterization of cross-platform misinformation diffusion

Advisor: Luca Luceri (Viterbi School of Engineering)
Students: William Lu , Zexun Yao , Duyen Nguyen , Jinyi Ye , Aaron Tom

Description

Fringe communities are often the sources of conspiracy theories and extreme ideas. Niche online platforms hosting such communities represent suitable incubators for reinforcing questionable stories and to ultimately push them into the mainstream. Over the years, information pathways from fringe to mainstream media have significantly increased, enabling the proliferation of harmful content. This project aims at developing novel network- and AI-based models for identifying and characterizing information pathways that enable the proliferation of potentially harmful content on online media channels. Mainstream social media (Twitter, Facebook, and Instagram), video streaming platforms (YouTube and Bitchute), niche platforms (Gab, 4chan, and Parler), and messaging apps (Telegram) will be considered to investigate how harmful narratives flow across diverse platforms and predict those that will gain traction on mainstream media.

Awards

  • Best Cyberphysical Data Science

  • Best Data Science Open and Sharing Practices

Students

Advisors

Skills Required by the team

  • Python
  • Statistics
  • Data Visualization
  • Social Network Analysis
Fall 2022 Featured Best Cyberphysical Data Science Best Data Science Open and Sharing Practices