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THE COMPUTATIONAL SOCIAL SCIENCE WORKSHOP PRESENTS</h3>
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CHRIS BAIL</h1>
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DOUGLAS AND ELLEN LOWEY ASSOCIATE PROFESSOR OF SOCIOLOGY AND PUBLIC POLICY</h3>
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DUKE UNIVERSITY</h3>
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The<span class="Apple-converted-space"> </span><a href="https://macss.uchicago.edu/content/computation-workshop" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">Computational
Social Science Workshop<span class="Apple-converted-space"> </span></a>at the University of Chicago cordially invites you to attend this week’s talk:</p>
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<a href="https://github.com/uchicago-computation-workshop/chris_bail/blob/master/2018__bail__exposure_to_opposing_views.pdf" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">EXPOSURE
TO OPPOSING VIEWS CAN INCREASE POLITICAL POLARIZATION: EVIDENCE FROM A LARGE-SCALE FIELD EXPERIMENT ON SOCIAL MEDIA</a></h2>
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<span style="box-sizing: border-box; font-weight: 700;">Abstract:</span><span class="Apple-converted-space"> </span>There is mounting concern that social media sites contribute to political polarization by creating “echo chambers” that insulate people from
opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at least three times each week about a range of social policy issues. One week later, we randomly assigned respondents to a treatment condition in
which they were offered financial incentives to follow a Twitter bot for one month that exposed them to messages produced by elected officials, organizations, and other opinion leaders with opposing political ideologies. Respondents were re-surveyed at the
end of the month to measure the effect of this treatment, and at regular intervals throughout the study period to monitor treatment compliance. We find that Republicans who followed a liberal Twitter bot became substantially more conservative post-treatment,
and Democrats who followed a conservative Twitter bot became slightly more liberal post-treatment. These findings have important implications for the interdisciplinary literature on political polarization as well as the emerging field of computational social
science.</p>
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THURSDAY, 4/5/2018</h4>
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11:00AM-12:20PM</h4>
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KENT 120</h4>
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A light lunch will be provided by Good Earth Catering Company.</p>
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<span style="box-sizing: border-box; font-weight: 700;">Chris Bail</span><span class="Apple-converted-space"> </span>is the Douglas and Ellen Lowey Associate Professor of Sociology and Public Policy at Duke. His research examines how non-profit organizations
and other political actors shape public opinion about controversial social issues by analyzing large groups of texts from newspapers, television, public opinion surveys, and social media sites such as Facebook and Twitter.</p>
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His research has been published by Princeton University Press, the Proceedings of the National Academy of Sciences, the American Sociological Review, and other leading publications. In 2017, he was one of 30 academics recognized by a prestigious Andrew Carnegie
Fellowship. His work has also been recognized by awards from the American Sociological Association, the Association for Research on Non-Profit Organizations and Voluntary Action, the Society for the Scientific Study of Religion, and the Society for Study of
Social Problems, and supported by the National Science Foundation, the Robert Wood Johnson Foundation, and the Russell Sage Foundation. His research has also been covered by major media outlets such as NBC News, National Public Radio, and the Washington Post.</p>
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Chris is also passionate about training the next generation of computational social scientists. He is the co-organizer of the 2017 Summer Institute in Computational Social Science at Princeton University and a founding member of Duke’s Interdisciplinary Data
Science Program.</p>
<span style="color: rgb(102, 102, 102); font-family: Raleway, sans-serif; font-size: 14px; text-size-adjust: auto;">Dr. Bail is currently studying the community-level predictors of violent extremism using Google search data, and how social networks influence
political polarization on Twitter.</span>
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The 2017-2018<span class="Apple-converted-space"> </span><a href="https://macss.uchicago.edu/content/computation-workshop" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">Computational
Social Science Workshop<span class="Apple-converted-space"> </span></a>meets each Thursday from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate students are welcome.</p>
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Students in the Masters of Computational Social Science program are expected to attend and join the discussion by posting a comment on the<span class="Apple-converted-space"> </span><a href="https://github.com/uchicago-computation-workshop/chris_bail/issues" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">issues
page<span class="Apple-converted-space"> </span></a>of the<span class="Apple-converted-space"> </span><a href="https://github.com/uchicago-computation-workshop/chris_bail" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">workshop’s
public repository on GitHub.</a><span class="Apple-converted-space"> </span>Further instructions are documented in the Computational Social Science Workshop’s<span class="Apple-converted-space"> </span><a href="https://github.com/uchicago-computation-workshop/README" style="box-sizing: border-box; background-color: transparent; color: rgb(66, 139, 202); text-decoration-line: none; transition: all 0.125s ease-in-out 0s;">README
on Github.</a></p>
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