All Research Areas
Research Areas
Year Published

48 Results

February 27, 2016

What’s in a Like? Attitudes and Behaviors Around Receiving Likes on Facebook

Computer-Supported Cooperative Work and Social Computing

What social value do Likes on Facebook hold? This research examines people’s attitudes and behaviors related to receiving one-click feedback in social media.

By: Lauren Scissors, Moira Burke, Steve Wengrovitz
February 27, 2016

Modeling Self-Disclosure in Social Networking Sites

ACM CSCW

Social networking sites (SNSs) offer users a platform to build and maintain social connections. Understanding when people feel comfortable sharing information about themselves on SNSs is critical to a good user experience, because self-disclosure helps maintain friendships and increase relationship closeness.

By: Yi-Chia Wang, Moira Burke, Robert Kraut
February 27, 2016

Once More with Feeling: Supportive Responses to Social Sharing on Facebook

Computer-Supported Cooperative Work and Social Computing

Using millions of de-identified Facebook status updates with poster-annotated feelings (e.g., feeling thankful or feeling worried), we examine the magnitude and circumstances in which people share positive or negative feelings and characterize the nature of the responses they receive.

By: Moira Burke, Mike Develin
January 13, 2016

Social Networks and Labor Markets: How Strong Ties Relate to Job Transmission On Facebook’s Social Network

Journal of Labor Economics

This is an observational study of the social networks of 1.4 million US Facebook users who list an employer in their profile.

By: Laura K. Gee, Jason Jones, Moira Burke
December 1, 2015

Internet Use and Psychological Well-Being: Effects of Activity and Audience

Communications of the ACM

Two lines of research fifteen years apart demonstrate that talking with close friends online is associated with improvements in social support, depression, and other measures of well-being. Talking with strangers and reading about acquaintances are not.

By: Robert Kraut, Moira Burke
April 26, 2014

Visually Impaired Users on an Online Social Network

ACM Conference on Human Factors in Computing Systems (CHI)

In this paper we present the first large-scale empirical study of how visually impaired people use online social networks, specifically Facebook. We identify a sample of 50K visually impaired users, a…

By: Shaomei Wu, Lada Adamic
April 26, 2014

Incentives to Participate in Online Research: An Experimental Examination of “Surprise” Incentives

ACM Conference on Human Factors in Computing Systems (CHI)

In this work, we present four experiments examining how two different kinds of ‘surprise’ financial incentives affect the rate of participation in a longitudinal study when participants are initially solicited with either an appeal to intrinsic motivation to participate in research or one that also offers extrinsic financial incentives.

By: Andrew Tresolini Fiore, Coye Cheshire, Lindsay Shaw Taylor, G.A. Mendelsohn
April 26, 2014

Growing Closer on Facebook: Changes in Tie Strength Through Site Use

ACM Conference on Human Factors in Computing (CHI)

Scientists debate whether people grow closer to their friends through social networking sites like Facebook, whether those sites displace more meaningful interaction, or whether they simply reflect existing ties.

By: Moira Burke, Robert Kraut
April 11, 2014

Designing and Deploying Online Field Experiments

International World Wide Web Conference (WWW)

Online experiments are widely used to compare specific design alternatives, but they can also be used to produce generalizable knowledge and inform strategic decision making. Doing so often requires sophisticated experimental designs, iterative refinement, and careful logging and analysis.

By: Eytan Bakshy, Dean Eckles, Michael Bernstein
April 7, 2014

Personalized Collaborative Clustering

International World Wide Web Conference (WWW)

We study the problem of learning personalized user models from rich user interactions. In particular, we focus on learning from clustering feedback (i.e., grouping recommended items into clusters), wh…

By: Yisong Yue, Chong Wang, Khalid El-Arini, Carlos Guestrin