The goal of this project is to determine if social media in general and one key social media platform in particular are shifting how people access civic information. Social media platforms have allowed a universe of alternative media to arise. These media create networks with millions of followers that, some argue, are increasingly detached from mainstream outlets. One platform, in particular, stands out in its ability to reach mass audiences while relying on distributed, networked forms of communication. In this project the prevalence of extremist content on this platform is quantified, audience engagement with that content is tracked, the pathways visitors follow to reach the universe of alternative media are identified, and these dynamics are contextualized in the broader frame of online exposure to such content including the web and other social media platforms. Findings are relevant to decisions on issues such as web use and the role of algorithms.

A unique observational dataset tracking domain-level and individual-level web browsing behavior, including platform-specific activity, is analyzed, using two different representative panels of the U.S. population during a period of four years. The analysis of these data allows measurement of the impact social media platforms have on exposure to extremist content. This project offers unprecedented findings by parsing web and social media activity for a specific population and reconstructing individual-level trajectories within platforms, thus reflecting different interests and choices but also the personalized recommendations received. By analyzing time-stamped data drawn for representative panels tracking observed behavior, this project provides a more fine-grained analysis of exposure to extremist content than past research that has relied on audits of recommendation algorithms or statistics collected from publicly available APIs. This award is jointly supported by the Sociology Program and the Secure and Trustworthy Cyberspace Program.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
2017655
Program Officer
Melanie Hughes
Project Start
Project End
Budget Start
2020-09-01
Budget End
2023-08-31
Support Year
Fiscal Year
2020
Total Cost
$249,548
Indirect Cost
Name
University of Pennsylvania
Department
Type
DUNS #
City
Philadelphia
State
PA
Country
United States
Zip Code
19104