Towards Understanding the Information Ecosystem Through the Lens of MultipleWeb Communities
Date Issued
October 2019
Author(s)
Advisor
Abstract
The Web consists of numerous Web communities, news sources, and services, which are
often exploited by various entities for the dissemination of false or otherwise malevolent
information. Yet, we lack tools and techniques to effectively track the propagation of
information across the multiple diverse communities, and to capture and model the
interplay and influence between them. Furthermore, we lack a basic understanding of
what the role and impact of some emerging communities and services on the Web
information ecosystem are, and how such communities are exploited by bad actors (e.g.,
state-sponsored trolls) that spread false and weaponized information.
In this thesis, we shed some light on the complexity and diversity of the information
ecosystem on the Web by presenting a typology that includes the various types of false
information, the involved actors as well as their possible motives. Then, we follow a datadriven
cross- platform quantitative approach to analyze billions of posts from Twitter,
Reddit, 4chan’s Politically Incorrect board (/pol/), and Gab, to shed light on: 1) how news
and image-based memes travel from one Web community to another and how we can
model and quantify the influence between the various Web communities; 2) characterizing
the role of emerging Web communities and services on the information ecosystem, by
studying Gab and two popular Web archiving services, namely the Wayback Machine and
archive.is; and 3) how popular Web communities are exploited by state-sponsored actors
for the purpose of spreading disinformation and sowing public discord.
In a nutshell, our analysis reveal that small fringe Web communities like 4chan’s /pol/ and
The Donald subreddit have a disproportionate influence on mainstream communities such
as Twitter with regard to the dissemination of news and image-based memes. We find
that Gab acts as the new hub for the alt-right community, while for Web archiving services
we find that they are popular on fringe Web communities and that they can be misused by
Reddit moderators in order to penalize ad revenue from news sources with conflicting
ideology. Finally, when studying state-sponsored actors, we find that they exhibit
substantial differences compared to random users, that their tactics change and evolve
over time, and that they were particularly influential in spreading news on popular
mainstream communities like Twitter and Reddit.
often exploited by various entities for the dissemination of false or otherwise malevolent
information. Yet, we lack tools and techniques to effectively track the propagation of
information across the multiple diverse communities, and to capture and model the
interplay and influence between them. Furthermore, we lack a basic understanding of
what the role and impact of some emerging communities and services on the Web
information ecosystem are, and how such communities are exploited by bad actors (e.g.,
state-sponsored trolls) that spread false and weaponized information.
In this thesis, we shed some light on the complexity and diversity of the information
ecosystem on the Web by presenting a typology that includes the various types of false
information, the involved actors as well as their possible motives. Then, we follow a datadriven
cross- platform quantitative approach to analyze billions of posts from Twitter,
Reddit, 4chan’s Politically Incorrect board (/pol/), and Gab, to shed light on: 1) how news
and image-based memes travel from one Web community to another and how we can
model and quantify the influence between the various Web communities; 2) characterizing
the role of emerging Web communities and services on the information ecosystem, by
studying Gab and two popular Web archiving services, namely the Wayback Machine and
archive.is; and 3) how popular Web communities are exploited by state-sponsored actors
for the purpose of spreading disinformation and sowing public discord.
In a nutshell, our analysis reveal that small fringe Web communities like 4chan’s /pol/ and
The Donald subreddit have a disproportionate influence on mainstream communities such
as Twitter with regard to the dissemination of news and image-based memes. We find
that Gab acts as the new hub for the alt-right community, while for Web archiving services
we find that they are popular on fringe Web communities and that they can be misused by
Reddit moderators in order to penalize ad revenue from news sources with conflicting
ideology. Finally, when studying state-sponsored actors, we find that they exhibit
substantial differences compared to random users, that their tactics change and evolve
over time, and that they were particularly influential in spreading news on popular
mainstream communities like Twitter and Reddit.
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