The success and failure of cultural products is mysterious. Best-selling books, blockbuster movies, and hit songs are much more successful than other products suggesting that these "superstars" are somehow special. Yet, despite these apparent differences, predicting which particular product will become the next-big-thing appears to be almost impossible. For example, the first Harry Potter book, which went on to become tremendously successful, was initially rejected by eight different publishers. In my dissertation I addressed this puzzling nature of success in a series of 4 web-based experiments involving more than 27,000 people. By creating a website where people could listen to and download new music, and more importantly where we could control the information that people had about the behavior of others, it was possible to experimentally explore the role of social influence in the creation of fads and thereby better understand success and failure in cultural markets.

Much of my other research involves social networks: describing their structure, understanding their consequences, and designing procedures to collect such information. For example, I continue to develop respondent-driven sampling, a network-based statistical method for the study of hidden populations that is currently being used by the Center for Disease Control in a study of drug injectors in 25 U.S. cities. Another project involves the development of new methods for the estimation of weak tie volume. In the future, I plan to integrate my research on social networks with my research on the sociology of culture and to explore creative uses of the Internet in social research.

CURRICULUM VITA (pdf)

SELECTED PUBLICATIONS:

Salganik, Matthew J., Peter S. Dodds, and Duncan J. Watts. 2006. ``Experimental study of inequality and unpredictability in an artificial cultural market.'' Science, 311:854-856.

Zheng, Tian, Matthew J. Salganik, and Andrew Gelman. 2006. ``How many people do you know in prison?: Using overdispersion in count data to estimate social structure in networks.'' Journal of the American Statistical Association, 101:409-423.

Salganik, Matthew J. 2006. ``Confidence intervals, design effects, and sample size calculation for respondent-driven sampling.'' Journal of Urban Health, 83:98-111.

Salganik, Matthew J. and Douglas D. Heckathorn. 2004. ``Sampling and estimation in hidden populations using respondent-driven sampling.'' Sociological Methodology, 34:193-239.