[Intelligence Seminar] April 12, 3:30pm:, Presentation by Matthew Salganik

[Dana Houston]

INTELLIGENCE SEMINAR
APRIL 12 AT 3:30PM, IN GHC 4303

SPEAKER: MATTHEW SALGANIK (Princeton University)
Host: Burr Settles
For meetings, contact Cathy Serventi (serventi at google.com)

WIKI SURVEYS: OPEN, ADAPTIVE, AND QUANTIFIABLE SOCIAL DATA COLLECTION
Joint work with Karen Levy

Research about attitudes and opinions is central to social science and
relies on two common methodological approaches: surveys and
interviews. While surveys allow researchers to quantify 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 hard to quantify. Advances
in computing technology now enable a hybrid approach, "wiki surveys",
that combines the quantifiability of a survey with the openness of an
interview. We draw on principles undergirding successful information
aggregation projects, such as Wikipedia and the Linux operating
system, to propose several theoretical criteria that wiki surveys
should satisfy. We then present results fromwww.allourideas.org, a
free and open source website that we created, which allows groups all
over the world to deploy wiki surveys. To date, over 800 wiki surveys
have been created, and they have collected over 30,000 ideas and 2
million votes. We describe some of the methodological challenges
involved in collecting and analyzing this type of data, and present
case studies of wiki surveys created by the New York City Mayor's
Office and the Organization for Economic Co-operation and Development
(OECD). The talk concludes a discussion of limitations and how some of
these limitations might be overcome with additional research.

BIO

Matthew Salganik is an Assistant Professor in the Department of
Sociology at Princeton University. His interests include social
networks, quantitative methods, and web-based social research. One
main area of his research has focused on developing network-based
statistical methods for studying populations most at risk for
HIV/AIDS. A second main area of work has been using the World Wide Web
to collect and analyze social data in innovative ways. 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 is funded by the National Science
Foundation, National Institutes of Health, Joint United Nations
Program for HIV/AIDS (UNAIDS), and Google.





-- 
Dana M. Houston
Language Technologies Institute
School of Computer Science
Carnegie Mellon University
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