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    Fri, Nov 18, 2016 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars

    Speaker: Pablo Barberá, School of International Relations at USC

    Talk Title: Less is more? How demographic sample weights can improve public opinion estimates based on Twitter data

    Abstract: Twitter data is widely acknowledged to hold great promise for the study of political behavior and public opinion. However, a key limitation in previous studies is the lack of information about the sociodemographic characteristics of individual users, which raises concerns about the validity of inferences based on this source of data. This paper addresses this challenge by employing supervised machine learning methods to estimate the age, gender, race, party affiliation, propensity to vote, and income of any Twitter user in the U.S. The training dataset for these classifiers was obtained by matching a large dataset of 1 billion geolocated Twitter messages with voting registration records and estimates of home values across 15 different states, resulting in a sample of nearly 250,000 Twitter users whose sociodemographic traits are known. To illustrate the value of this approach, I offer three applications that use information about the predicted demographic composition of a random sample of 500,000 U.S. Twitter users. First, I explore how attention to politics varies across demographics groups. Then, I apply multilevel regression and postratification methods to recover valid estimate of presidential and candidate approval that can serve as early indicators of public opinion changes and thus complement traditional surveys. Finally, I demonstrate the value of Twitter data to study questions that may suffer from social desirability bias.

    Biography: Pablo Barberá joined the School of International Relations at USC as an Assistant Professor in 2016, after receiving his PhD in political science from New York University and spending a year as a Post-Doctoral Fellow at the Center for Data Science in New York University. His research interests include computational methods in the social sciences, automated text analysis, and social network analysis. He applies these methods to the study of social media and politics, comparative electoral behavior and collective action, and political representation. His work has been published in Political Analysis, PLOS ONE, Psychological Science, the Journal of Computer-Mediated Communication, Social Media + Society, and Social Science Computer Review. His current research agenda focuses on the role of social media platforms in the growth of social protests, the measurement of public opinion and political behavior using digital trace data, and how exposure to political violence and governments' counter-messages on social media affects ideological extremism and support for terrorist groups.

    Host: Emilio Ferrara

    Location: Information Science Institute (ISI) - 11th floor large conference room

    Audiences: Everyone Is Invited

    Contact: Kary LAU

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