Matthew J. Salganik | Academic Influence

Matthew J. Salganik's AcademicInfluence.com Rankings

Matthew J. Salganik

Sociology

#1495

World Rank

#1696

Historical Rank

#557

USA Rank

sociology Degrees

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Sociology

Matthew J. Salganik's Degrees

PhD Sociology Columbia University
Bachelors Sociology University of California, Berkeley

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Why Is Matthew J. Salganik Influential?

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According to Wikipedia, Matthew Jeffrey Salganik is an American sociologist and professor of sociology at Princeton University with a special interest on social networks and computational social science. Career Salganik received his bachelor's degree in mathematics at Emory University in 1998. He proceeded to get his master's degree in sociology at Cornell University in 2003, where he also lived in the Telluride House. He finished his Ph.D. in sociology at Columbia University in 2007. Salganik was hired by Princeton in 2007 as an assistant professor and was promoted to full professor in 2013. Alongside this, he also currently serves as the Director of the Center for Information Technology Policy. Salganik is affiliated with interdisciplinary research centers at Princeton, such as the Office for Population Research, the Center for Information Technology Policy, the Center for Health and Wellbeing, and the Center for Statistics and Machine Learning. In 2017, he and Chris Bail co-founded Summer Institute in Computational Social Science , an annual program that provides learning and research opportunities for students, faculty, and researchers across the world within the realm of data science and social science.

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Matthew J. Salganik's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market (2006) (1918)
5. Sampling and Estimation in Hidden Populations Using Respondent-Driven Sampling (2004) (1364)
Variance Estimation, Design Effects, and Sample Size Calculations for Respondent-Driven Sampling (2006) (404)
Assessing respondent-driven sampling (2010) (356)
Bit by Bit: Social Research in the Digital Age (2019) (344)
Leading the Herd Astray: An Experimental Study of Self-fulfilling Prophecies in an Artificial Cultural Market (2008) (251)
How Many People Do You Know in Prison? (2006) (206)
Diagnostics for respondent‐driven sampling (2012) (194)
How Many People Do You Know?: Efficiently Estimating Personal Network Size (2010) (192)
Respondent‐driven sampling as Markov chain Monte Carlo (2009) (192)
Strengthening the Reporting of Observational Studies in Epidemiology for respondent-driven sampling studies: “STROBE-RDS” statement (2015) (181)
Computational social science: Obstacles and opportunities (2020) (141)
Counting hard-to-count populations: the network scale-up method for public health (2010) (134)
Wiki Surveys: Open and Quantifiable Social Data Collection (2012) (134)
Measuring the predictability of life outcomes with a scientific mass collaboration (2020) (134)
Web-Based Experiments for the Study of Collective Social Dynamics in Cultural Markets (2009) (126)
Assessing Network Scale-up Estimates for Groups Most at Risk of HIV/AIDS: Evidence From a Multiple-Method Study of Heavy Drug Users in Curitiba, Brazil (2011) (94)
Integrating explanation and prediction in computational social science (2021) (81)
Commentary: Respondent-driven Sampling in the Real World. (2012) (71)
The game of contacts: Estimating the social visibility of groups (2011) (57)
Generalizing the Network Scale-up Method (2014) (49)
Quantity Versus Quality: A Survey Experiment to Improve the Network Scale-up Method (2016) (29)
Introduction to the Special Collection on the Fragile Families Challenge (2019) (23)
Privacy, Ethics, and Data Access: A Case Study of the Fragile Families Challenge (2018) (20)
Successes and Struggles with Computational Reproducibility: Lessons from the Fragile Families Challenge (2019) (20)
Social influence: the puzzling nature of success in cultural markets (2009) (16)
The Network Survival Method for Estimating Adult Mortality: Evidence From a Survey Experiment in Rwanda (2016) (13)
Respondent-driven Sampling in the Real World (2012) (12)
Success and failure in cultural markets (2007) (12)
Consensus-based guidance for conducting and reporting multi-analyst studies (2021) (10)
Explanation, prediction, and causality: Three sides of the same coin? (2018) (7)
Improving metadata infrastructure for complex surveys:  Insights from the Fragile Families Challenge (2018) (7)
Improving Metadata Infrastructure for Complex Surveys: Insights from the Fragile Families Challenge (2019) (4)
Estimating the Size of Hidden Populations Using the Generalized Network Scale-Up Estimator (2014) (4)
Prediction, Machine Learning, and Individual Lives: an Interview with Matthew Salganik (2020) (2)
FINAL SAMPLE DESIGN FOR THE CENSUS 2000 ACCURACY AND COVERAGE EVALUATION (2002) (2)
Scaling up experimental social, behavioral, and economic science (2021) (2)
Cascades of culture: Exploring extreme variation and extreme unpredictability with modeling and experiments (2005) (1)
Sociology 323: Social networks (2007) (0)
Self-fulfilling prophecies in cultural markets: An experimental approach (2006) (0)
Predicting the future of society (2023) (0)
Limits to prediction : pre (2020) (0)
Introduction to Wiki Surveys (2012) (0)

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