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.

Peer Reviewed Computer Science Conference
Publication date: 
05/2017
Authors: 
Will Hobbs
Lisa Friedland
Kenneth Joseph
Oren Tsur
Stefan J. Wojcik
David Lazer

Over the past 12 years, nearly 20 U.S. States have adopted voter photo identification laws, which require voters to show a picture ID to vote. These laws have been challenged in numerous lawsuits, resulting in a variety of court decisions and, in several instances, revised legislation.

Peer Reviewed Computer Science Conference
Publication date: 
05/2017
Authors: 
Oren Tsur
David Lazer

Understanding the factors of network formation is a fundamental aspect in the study of social dynamics. Online activity provides us with abundance of data that allows us to reconstruct and study social networks. Statistical inference methods are often used to study network formation. Ideally, statistical inference allows the researcher to study the significance of specific factors to the network formation.

OP ED
Publication date: 
05/2017

We know a lot about fake news. It's an old problem. Academics have been studying it - and how to combat it - for decades. In 1925, Harper's Magazine published "Fake News and the Public," calling it's spread via new communication technoloies "a source of unprecedented dange."

Journal Article
Publication date: 
05/2017
Authors: 
Philipp Hunziker
Lars-Erik Cederman

"A large body of literature claims that oil production increases the risk of civil war. However, a growing number of skeptics argue that the oil-conflict link is not casual, but merely an artifact of flawed research designs. This article reevaluates whether - and where - oil causes conflict by employing a novel identification strategy based on the geological determinants of hydrocarbon reserves.

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.

Keywords: 
election prediction
crowdsourcing
Wikipedia
politics
social media
communication studies
Peer Reviewed Computer Science Conference
Publication date: 
10/2012
Authors: 
Nan Cao
Yu-Ru Lin
Xiaohua Sun
David Lazer
Shixia Liu
Huamin Qu

When and where is an idea dispersed? Social media, like Twitter, has been increasingly used for exchanging information, opinions and emotions about events that are happening across the world. Here we propose a novel visualization design, "Whisper," for tracing the process of information diffusion in social media in real time.

Keywords: 
spatiotemporal patterns
Information visualization
information diffusion
contagion
social media
microblogging
Peer Reviewed Computer Science Conference
Publication date: 
07/2012
Authors: 
Yu-Ru Lin
James P. Bagrow
David Lazer

Social media, such as blogs, are often seen as democratic entities that allow more voices to be heard than the conventional mass or elite media. Some also feel that social media exhibits a balancing force against the arguably slanted elite media. A systematic comparison between social and mainstream media is necessary but challenging due to the scale and dynamic nature of modern communicatiion.

Peer Reviewed Computer Science Conference
Publication date: 
09/2013
Authors: 
Yaniv Altshuler
Michael Fire
Erez Shmueli
Yuval Elovici
Alfred Bruckstein
Alex `Sandy' Pentland
David Lazer

In this paper we discuss the analysis of mobile networks communication patterns in the presence of some anomalous "real world event." We argue that given limited analysis resources (namely, limited number of network edges we can analyze), it is best to select edges that are located around 'hubs' in the network, resulting in an improved ability to detect such events.

Keywords: 
Mobile Networks
Anomalies Detection
Emergencies
Behavior Modeling
Peer Reviewed Computer Science Conference
Publication date: 
04/2017
Authors: 
Drew B. Margolin
Yu-Ru Lin
Devon Brewer
David Lazer

This position paper argues for the establishment of a "Rosetta Stone" that maps behavioral signatures of population behavior to meaningful social categories. We propose a method for accomplishing this through the deployment of behavioral tracking combined with survey questionnaires. The goal is to identify salient patterns of behavioral activity and ask subjects to "explain" these patterns through their survey responses.