Using Internet search data to examine the relationship between anti-Muslim and pro-ISIS sentiment in U.S. counties.
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Recent terrorist attacks by first- and second-generation immigrants in the United States and Europe indicate that radicalization may result from the failure of ethnic integration-or the rise of intergroup prejudice in communities where "home-grown" extremists are raised. Yet, these community-level drivers are notoriously difficult to study because public opinion surveys provide biased measures of both prejudice and radicalization. We examine the relationship between anti-Muslim and pro-ISIS (Islamic State of Iraq and Syria) Internet searches in 3099 U.S. counties between 2014 and 2016 using instrumental variable models that control for various community-level factors associated with radicalization. We find that anti-Muslim searches are strongly associated with pro-ISIS searches-particularly in communities with high levels of poverty and ethnic homogeneity. Although more research is needed to verify the causal nature of this relationship, this finding suggests that minority groups may be more susceptible to radicalization if they experience discrimination in settings where they are isolated and therefore highly visible-or in communities where they compete with majority groups for limited financial resources. We evaluate the validity of our findings using several other data sources and discuss the implications of our findings for the study of terrorism and intergroup relations, as well as immigration and counterterrorism policies.
Published Version (Please cite this version)10.1126/sciadv.aao5948
Publication InfoBail, Christopher; Merhout, Friedolin; & Ding, Peng (2018). Using Internet search data to examine the relationship between anti-Muslim and pro-ISIS sentiment in U.S. counties. Science advances, 4(6). pp. eaao5948. 10.1126/sciadv.aao5948. Retrieved from https://hdl.handle.net/10161/17349.
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Douglas and Ellen Lowey Associate Professor
Chris Bail is the Douglas and Ellen Lowey Associate Professor of Sociology and Public Policy at Duke. His research examines political polarization, culture and social psychology using tools from the emerging field of computational social science (e.g. digital trace data from social media sites, automated text analysis, and machine learning)Chris is the recipient of a Guggenheim Fellowship, a Carnegie Fellowship, and numerous awards from the American Sociological Association, the Asso
I am a PhD candidate in the Department of Sociology at Duke University where I explore how computational methods provide a new lens to view longstanding social science debates. When I am not pondering the potential inherent in the wealth of digital trace data, I dabble in experimental and conventional survey methods. Before starting the doctoral program at Duke, I earned a BA from <a href="https://www.fu-berlin.de/en/ind
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