Towards Understanding the Information Ecosystem Through the Lens of Multiple Web Communities
Savvas Zannettou

TL;DR
This paper analyzes how false information and memes spread across diverse Web communities, revealing influence patterns, the role of emerging platforms, and exploitation by malicious actors through a data-driven, cross-platform approach.
Contribution
It introduces a typology of false information and employs a quantitative analysis of billions of posts across multiple platforms to understand influence and exploitation in the Web ecosystem.
Findings
Fringe communities like 4chan's /pol/ influence mainstream platforms.
Gab acts as a hub for the alt-right community.
State-sponsored actors significantly spread disinformation on popular platforms.
Abstract
The Web consists of numerous Web communities, news sources, and services, which are often exploited by various entities for the dissemination of false information. Yet, we lack tools and techniques to effectively track the propagation of information across the multiple diverse communities, and to model the interplay and influence between them. Also, we lack an understanding of what the role and impact of emerging communities and services on the Web are, and how such communities are exploited by bad actors that spread false and weaponized information. In this thesis, we study the information ecosystem on the Web by presenting a typology that includes the various types of false information, the involved actors and their possible motives. Then, we follow a data-driven cross-platform quantitative approach to analyze billions of posts from Twitter, Reddit, 4chan's /pol/, and Gab, to shed…
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Taxonomy
TopicsMisinformation and Its Impacts · Spam and Phishing Detection · Complex Network Analysis Techniques
