MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways

TL;DR

MIDDAG is an interactive system that visualizes COVID-19 news information flow on social media, providing insights into community susceptibility, propagation patterns, and forecasting dissemination at a higher level.

Contribution

It introduces a novel system for visualizing and analyzing social media information diffusion with community detection and propagation forecasting capabilities.

Findings

Identifies community-level information flow patterns

Provides insights into user susceptibility and opinions

Enables forecasting of information dissemination

Abstract

We present MIDDAG, an intuitive, interactive system that visualizes the information propagation paths on social media triggered by COVID-19-related news articles accompanied by comprehensive insights, including user/community susceptibility level, as well as events and popular opinions raised by the crowd while propagating the information. Besides discovering information flow patterns among users, we construct communities among users and develop the propagation forecasting capability, enabling tracing and understanding of how information is disseminated at a higher level.