Center Events

Wiki surveys: Open and quantifiable social data collection

April 25, 2014 | Annenberg Room 500

Annenberg School Colloquium Series and Warren Center for Network and Data Sciences present:

Wiki surveys: Open and quantifiable social data collection
Friday, April 25th. 12:00-1:30.
Annenberg Rm.500
Matt Salganik
Professor of Sociology, Princeton University

Research about attitudes and opinions is central to social science and relies on two common methodological approaches: surveys and interviews. While surveys enable the quantification of large amounts of information quickly and at a reasonable cost, they are routinely criticized for being “top-down” and rigid. In contrast, interviews allow unanticipated information to “bubble up” directly from respondents, but are slow, expensive, and difficult to quantify. Advances in computing technology now enable a hybrid approach that combines the quantifiability of a survey and the openness of an interview; we call this new class of data collection tools wiki surveys. Drawing on principles underlying successful information aggregation projects, such as Wikipedia, we propose three general criteria that wiki surveys should satisfy: they should be greedy, collaborative, and adaptive. We then present results from, a free and open-source website we created that enables groups all over the world to deploy wiki surveys. To date, more than 4,000 wiki surveys have been created, and they have collected over 200,000 ideas and 5 million votes. We describe the methodological challenges involved in collecting and analyzing this type of data and present a case study of a wiki survey created by the New York City Mayor’s Office. [Joint work with Karen E.C. Levy]

Matthew Salganik is Professor of Sociology at Princeton University (on leave) and Senior Researcher at Microsoft Research New York City. His interests include social networks, quantitative methods, and web-based social research. Salganik’s research has been published in journals such as Science, PNAS, Sociological Methodology, and Journal of the American Statistical Association. His papers have won the Outstanding Article Award from the Mathematical Sociology Section of the American Sociological Association and the Outstanding Statistical Application Award from the American Statistical Association. Popular accounts of his work have appeared in the New York Times, Wall Street Journal, Economist, and New Yorker. Salganik’s research has been funded by the National Science Foundation, National Institutes of Health, Joint United Nations Program for HIV/AIDS (UNAIDS), and Google.