Professor in Political Science and Computer and Information Science

David Lazer

Research Tracks Overview

Journal Article
Publication date: 
04/2017
Authors: 
David Lazer
Jason Radford

Social life continues to increasingly occur in digital environments and to be mediatedby digital systems. Big Data represents the data being generated by the digitization of social life which we break down into three domains: digital life, digitalized life, and digited traces. We argue that there is enormous potential in using big data to study a variety of phenomena that remain difficult to observe.

Peer Reviewed Computer Science Conference
Publication date: 
10/2015
Authors: 
Chloe Kliman-Silver
Ancsa Hannak
David Lazer
Christo Wilson
Alan Mislove

To cope with the immense amount of content on the web, search engines often use complex algorithms to personalize search results for individual users. However, personalization of search results has led to worries about the Filter Bubble Effect, where the personalization algorithm decides that some useful information is irrelevant to the user, and thus prevents them from locating it.

Keywords: 
Search
Personalization
Geolocation
Internet Filter Bubble
Peer Reviewed Computer Science Conference
Publication date: 
07/2015
Authors: 
Oren Tsur
Dan Calacci
David Lazer

Framing is a sophisticated form of discourse in which the speaker tries to induce a cognitive bias through consistent linkage between a topic and a specific context (frame). We build on political science and communication theory and use probabilistic topic models combined with time series regression analysis (autoregressive distributed-lag models) to gain insights about the language dynamics in the political processes.

Peer Reviewed Computer Science Conference
Publication date: 
10/2014
Authors: 
Jason Radford
Brian Keegan
Jefferson Hoye
Ceyhun Karbeyaz
Katherine Ognyanova
Brooke Foucault Welles
Weleed Meleis
David Lazer

Volunteer Science is an online platform enabling anyone to participate in social science research. The goal of Volunteer Science is to build a thriving community of research participants and social science researchers for Massively Open Online Social Experiments ("MOOSEs").

Keywords: 
Online experiments
group experiments
replication
traveling salesman problem
hidden profile
exploration-exploitation
Peer Reviewed Computer Science Conference
Publication date: 
11/2014
Authors: 
Ancsa Hannak
Gary Soeller
David Lazer
Alan Mislove
Christo Wilson

Today, many e-commerce websites personalize their content, including Netix (movie recommendations), Amazon (product suggestions), and Yelp (business reviews). In many cases, personalization provides advantages for users: for example, when a user searches for an ambiguous query such as \router," Amazon may be able to suggest the woodworking tool instead of the networking device.

Keywords: 
Search
Personalization
E-commerce
Price discrimination
Peer Reviewed Computer Science Conference
Publication date: 
05/2013
Authors: 
Ancsa Hannak
Piotr Sapiezynski
Arash Molavi Kakhki
Balachander Krishnamurthy
David Lazer
Alan Mislove
Christo Wilson

Web search is an integral part of our daily lives. Recently, there has been a trend of personalization in Web search, where different users receive different results for the same search query. The increasing personalization is leading to concerns about Filter Bubble effects, where certain users are simply unable to access information that the search engines' algorithm decides is irrelevant.

Keywords: 
Personalization
Web search
Measurement
Peer Reviewed Computer Science Conference
Publication date: 
05/2013
Authors: 
Yu-Ru Lin
Drew B. Margolin
Brian Keegan
David Lazer

Social media have been employed to assess public opinions on events, markets, and policies. Most current work focuses on either developing aggregated measures or opinion extraction methods like sentiment analysis. These approaches suffer from unpredictable turnover in the participants and the information they react to, making it difficult to distinguish meaningful shifts from those that follow from known information.

Keywords: 
real time system
social meter
public opinion
data-driven journalism
process inference
computational social science
Peer Reviewed Computer Science Conference
Publication date: 
05/2013
Authors: 
Yu-Ru Lin
Drew B. Margolin
Brian Keegan
Andrea Baronchelli
David Lazer

We examine the growth, survival, and context of 256 novel hashtags during the 2012 U.S. presidential debates. Our analysis reveals the trajectories of hashtag use fall into two distinct classes: "winners" that emerge more quickly and are sustained for longer periods of time than other "also-rans" hashtags.

Peer Reviewed Computer Science Conference
Publication date: 
02/2013
Authors: 
Yu-Ru Lin
Drew B. Margolin
Brian Keegan
Mauro Martino
Sasha Goodman
David Lazer

In this interactive poster, we describe a system we designed for identifying and tracking the behavior of distinct audiences in social media streams.

Keywords: 
social media
real-time analysis
audience behavior
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.

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