Professor in Political Science and Computer and Information Science

David Lazer

Computational Social Science

Big Data: big insights into human behavior

One of the emerging memes of recent years has been around “big data”—the development of very large data sets around many domains. In the area of human behavior, there are these vast reservoirs of information about our lives that have accumulated, in everywhere from our inboxes to cellular phone companies to credit card companies, to the Internet, where a large fraction of all human expression is now taking place for all to see.

These data must surely offer awesome insights into both individual and human behavior, and our perspective on both will change as a result.

Computational Social Science: Publications List

Publications list

N. Cao, Y. Lin, X. Sun, D. Lazer, S. Liu and H. Qu, “Whisper: Tracing the Spatiotemporal Process of Information Diffusion in Real Time,” IEEE Information Visualization 2012, (also forthcoming in IEEETransactions on Visualization and Computer Graphics).

Y. Lin, J. Bagrow, and D. Lazer, “More Voices than Ever? Quantifying Media Bias in Networks,” ICWSM-11, Barcelona, 2011.

A Madan, S. Moturu, D. Lazer, and A Pentland “Social Sensing: Obesity, unhealthy Eating and Exercise in Face-to-face Networks”, proceedings of ACM Wireless Health 2010, San Diego, 2010.

A Madan, M. Cebrian, D. Lazer, and A. Pentland “Social Sensing to Model Epidemiological Behavior Change”, Proceedings of ACM Ubicomp 2010, Copenhagen (Nominated for Best Paper), 2010.

N. Eagle, A. Pentland, and D. Lazer, “Inferring friendship structure using mobile phone data,” Proceedings of the National Academy of Sciences, August 17, 2009.

D. Lazer, I. Mergel, and A. Friedman, “Co-citation of prominent social network articles in sociology journals: The evolving canon,” Connections, April, 2009.

D. Lazer, A. Pentland, L. Adamic, S. Aral, A-L Barabasi, D. Brewer, N. Christakis, N. Contractor, J. Fowler, M. Gutmann, T. Jebara, G. King, M. Macy, D. Roy, and M. Van Alstyne “Computational Social Science,” Science, February 6, 2009. 

J.-P. Onnela, J. Saramäki, J. Hyvönen, G. Szabó, D. Lazer, K. Kaskil, J. Kertész, and A.-L. Barabási,  “Structure and tie strengths in mobile communication networks,” Proceedings of the National Academy of Sciences, May 1, 2007.

Journal Article
Publication date: 
09/2016
Authors: 
Wei Wang
Ryan P. Kennedy
David Lazer
Naren Ramakrishnan

There have been serious efforts over the past 40 years to use newspaper articles to create global scale databases of events occurring in every corner of the world, to help understand and shape responses to global problems.

Journal Article
Publication date: 
04/2015
Authors: 
Ryan P. Kennedy
Brian Keegan
Eric Forbush
David Lazer

This article advocates a lesson plan for introductory comparative politics and election courses. The authors argue that Wikipedia (yes, Wikipedia) provides a unique platform for improving learning outcomes and a useful social good from traditional student papers on elections.

Journal Article
Publication date: 
05/2015
Authors: 
Jameson L. Toole
Yu-Ru Lin
Erich Muehlegger
Daniel Shoag
Marta C Gonzalez
David Lazer

Can data from mobile phones be used to observe economic shocks and their consequences at multiple scales? Here we present novel methods to detect mass layoffs, identify individuals affected by them and predict changes in aggregate unemployment rates using call detail records (CDRs) from mobile phones.

Keywords: 
unemployment
computational social science
social networks
mobility
complex systems
Journal Article
Publication date: 
05/2015
Authors: 
David Lazer

Humanity is in the early stages of the rise of social algorithms: programs that size us up, evaluate what we want, and provide a customized experience. This quiet but epic paradigm shift is fraught with social and policy implications. The evolution of Google exemplifies this shift.

Journal Article
Publication date: 
06/2015
Authors: 
Yu-Ru Lin
Drew B. Margolin
David Lazer

The increasing abundance of digital textual archives provides an opportunity for understanding human social systems. Yet the literature has not adequately considered the disparate social processes by which texts are produced.

Journal Article
Publication date: 
08/2015
Authors: 
Drew B. Margolin
Brian Keegan
Sasha Goodman
Yu-Ru Lin
David Lazer

The use of socio-technical data to predict elections is a growing research area. We argue that election prediction research suffers from under-specified theoretical models that do not properly distinguish between 'poll-like' and 'prediction market-like' mechanisms understand findings.

Journal Article
Publication date: 
12/2016
Authors: 
Jason Radford
Andy Pilny
Ashley Reichelmann
Brian Keegan
Brooke Foucault Welles
Jefferson Hoye
Katherine Ognyanova
Weleed Meleis
David Lazer

Experimental Research in traditional laboratories comes at a significant logistic and financial cost while drawing data from demographically narrow populations. The growth of online methods of research has resulted in effective means for social psychologists to collect large-scale survey-based data in a cost-effective and timely manner.

Journal Article
Publication date: 
02/2017
Authors: 
Ryan P. Kennedy
Stefan Wojcik
David Lazer

This study reports the results of a  multiyear program to predict direct executive elections in a variety of countries from globally pooled data. We developed prediction models by means of an election data set covering 86 countries and more than 500 elections, and a separate data set with extensive polling data from 146 election rounds. We also participated in two live forecasting experiments.

Media Coverage And Appearance
Publication date: 
08/2016

Donald Trump has become well known for his shoot-from-the-hip tweeting style. Lots of insults, lots of rants and lots of energy. Data scientists who have examined all of Trump's tweets over time found he has some very clear Twitter strategies and tactics that, in many ways, have been working.

Keywords: 
Trump
Twitter