Josh Pasek is Assistant Professor of Communication Studies and Faculty Associate in the Center for Political Studies at the University of Michigan. His substantive research explores how new media and psychological processes each shape political attitudes, public opinion, and political behaviors. Josh also examines issues in the measurement of public opinion including techniques for incorporating social trace data as a means of tracking attitudes and behaviors. Current research evaluates whether the use of online social networking sites such as Facebook and Twitter might be changing the political information environment, and assesses the conditions under which nonprobability samples, such as those obtained from big data methods or samples of Internet volunteers can lead to conclusions similar to those of traditional probability samples. His work has been published in Public Opinion Quarterly, Political Communication, Communication Research, and the Journal of Communication among other outlets. He also maintains two R packages for producing survey weights (anesrake) and analyzing weighted survey data (weights).
Dr. Song is interested in methodological developments related to modelling, statistical inference and applications in biomedical sciences. One of his current research areas concerns the development of statistical methodology and algorithm for fusion learning and homogeneity pursuit in data integration to address various analytic challenges from data heterogeneity. Another focus of his current research is on the regression analysis of networked data, with applications to electroencephalogram data analysis for the understanding of human growth and development.