Publications

Publication date: 
09/2017
Authors: 
Daizhuo Chen
Samuel Fraiberger
Robert Moakler
Foster Provost

Recent studies show the remarkable power of fine-grained information disclosed by users on social network sites to infer users’ personal characteristics via predictive modeling. Similar fine-grained data are being used successfully in other commercial applications.

Keywords: 
predictive modeling; transparency; privacy; comprehensibility; inference; control
Publication date: 
09/2017
Authors: 
Heinrich H. Nax
Stefano Balietti
Ryan O. Murphy
Dirk Helbing

Real-world institutions dealing with social dilemma situations are based on mechanisms that are rarely implemented without flaw. Usually real-world mechanisms are noisy and imprecise, that is, which we call ‘fuzzy’. We therefore conducted a novel type of voluntary contributions experiment where we test a mechanism by varying its fuzziness. We focus on a range of fuzzy mechanisms we call ‘meritocratic matching’.

Keywords: 
inequality
efficiency
public-good game
noise
institution
meritocracy
Publication date: 
09/2017
Authors: 
Kenny Joseph
Lisa Friedland
Will Hobbs
David Lazer
Oren Tsur

Manual annotations are a prerequisite for many applications of machine learning. However, weaknesses in the annotation process itself are easy to overlook. In particular, scholars often choose what information to give annotators without examining these decisions empirically. For subjective tasks such as sentiment analysis, sarcasm, and stance detection, such choices can impact results.

Publication date: 
08/2017
Authors: 
B.R. Jasny
N. Wigginton
M. McNutt
T. Bubela
S. Buck
R. Cook-Deegan
T. Gardner
B. Hanson
C. Hustad
V. Kiermer
David Lazer
A. Lupier
A. Manrai
L. McConnell
K. Noonan
Publication date: 
08/2017
Authors: 
John Wihbey
Kenny Joseph
Thalita Coleman
David Lazer

The present work proposes the use of social media as a tool for better understanding the relationship between a journalists' social network and the content they produce. Specifically, we ask: what is the relationship between the idealogical leaning of a journalist's social network on Twitter and the news content he or she produces?

Keywords: 
Twitter
journalism
filter bubble
echo chambers
computational social science
Publication date: 
05/2017
Authors: 
Matthew A. Baum
David Lazer

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 technologies "a source of unprecedented danger."

Publication date: 
05/2017
Authors: 
Will Hobbs
Lisa Friedland
Oren Tsur
Stefan 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.

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.

Publication date: 
04/2017
Authors: 
David Lazer
Publication date: 
04/2017
Authors: 
David Lazer
Oren Tsur
Katherine Ognyanova
Ryan Kennedy

Publications by type

Journal Article