Presentations

Big Data is Not About the Data!, at Indiana University, Thursday, March 23, 2017:

The spectacular progress the media describes as "big data" has little to do with the data.  Data, after all, is becoming commoditized, less expensive, and an automatic byproduct of other changes in organizations and society. More data alone doesn't generate insights; it often merely makes data analysis harder. The real revolution isn't about the data, it is about the stunning progress in the statistical and other methods of extracting insights from the data. I illustrate these points with a wide range of examples from research I've participated in, including forecasting the solvency of… Read more about Big Data is Not About the Data!

How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument, at MIT Distinguished Lecture Series, IDSS, Tuesday, March 7, 2017:

This talk is based on this paper (forthcoming in the American Political Science Review), by Jen Pan, Molly Roberts, and me, along with a brief summary of our previous work (2014 in Science here, and 2013 in the APSR here). Here's an abstract: The Chinese government has long… Read more about How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument

How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument, at Duke University, Machine Learning Seminar, Wednesday, March 1, 2017:

This talk is based on this paper (forthcoming in the American Political Science Review), by Jen Pan, Molly Roberts, and me, along with a brief summary of our previous work (2014 in Science here, and 2013 in the APSR here). Here's an abstract: The Chinese government has long… Read more about How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument

How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument, at Washington University, St. Louis, Monday, February 13, 2017:

This talk is based on this paper (forthcoming in the American Political Science Review), by Jen Pan, Molly Roberts, and me, along with a brief summary of our previous work (2014 in Science here, and 2013 in the APSR here). Here's an abstract: The Chinese government has long… Read more about How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument

Simplifying Matching Methods for Causal Inference, at Harvard School of Public Health, Kresge Room G2, Thursday, January 26, 2017:

This talk introduces methods of matching for causal inference that are simpler, more powerful, and easier to understand than prior approaches. Software is available to implement everything discussed. Copies of my articles on the subject are available at my website.

How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument, at University of Wisconsin-Madison, Monday, January 23, 2017:

This talk is based on this paper (forthcoming in the American Political Science Review), by me, Jennifer Pan, and Margaret Roberts, along with a brief summary of our previous work. Here's an abstract: The Chinese government has long been suspected of hiring as many as 2,000,000 people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-… Read more about How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument

An Improved Method of Automated Nonparametric Content Analysis for Social Science, at Texas A&M Inaugural STATA Lecture, Thursday, January 19, 2017:

A vast literature in computer science and statistics develops methods to automatically classify textual documents into chosen categories. In contrast, social scientists are often more interested in aggregate generalizations about populations of documents --- such as the percent of social media posts that speak favorably of a candidate's foreign policy. Unfortunately, trying to maximize the percent of individual documents correctly classified often yields biased estimates of statistical aggregates. Fortunately, classification is neither a necessary nor even a desirable step in estimating… Read more about An Improved Method of Automated Nonparametric Content Analysis for Social Science

Big Data is Not About the Data!, at Shanghai Jiao Tong University, Wednesday, January 4, 2017:

The spectacular progress the media describes as "big data" has little to do with the data.  Data, after all, is becoming commoditized, less expensive, and an automatic byproduct of other changes in organizations and society. More data alone doesn't generate insights; it often merely makes data analysis harder. The real revolution isn't about the data, it is about the stunning progress in the statistical and other methods of extracting insights from the data. I illustrate these points with a wide range of examples from research I've participated in from the quantitative social sciences,… Read more about Big Data is Not About the Data!

An Improved Method of Automated Nonparametric Content Analysis for Social Science, at New York University, Text as Data Speaker Series, Thursday, December 1, 2016:

A vast literature in computer science and statistics develops methods to automatically classify textual documents into chosen categories. In contrast, social scientists are often more interested in aggregate generalizations about populations of documents --- such as the percent of social media posts that speak favorably of a candidate's foreign policy. Unfortunately, trying to maximize the percent of individual documents correctly classified often yields biased estimates of statistical aggregates. Fortunately, classification is neither a necessary nor even a desirable step in estimating… Read more about An Improved Method of Automated Nonparametric Content Analysis for Social Science

How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument, at Pacific Information Operations Symposium, Honolulu, Tuesday, November 8, 2016:

This talk is based on this paper, by me, Jennifer Pan, and Margaret Roberts, along with a brief summary of our previous work. Here's an abstract: The Chinese government has long been suspected of hiring as many as 2,000,000 people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-called "50c party" posts vociferously argue for the government's… Read more about How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, not Engaged Argument

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