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102 Results

May 7, 2016

Changes in Engagement Before and After Posting to Facebook

CHI 2016

We are interested in the ways in which posting content changes individuals’ engagement with Facebook. The study augments previous knowledge about uses and gratifications from posting on social network sites by focusing on short-term activity of contributors.

By: Nir Grinberg, Alex Dow, Lada Adamic, Mor Naaman
April 11, 2016

People and Cookies: Imperfect Treatment Assignment in Online Experiments

WWW 2016

Identifying the same internet user across devices or over time is often infeasible. This presents a problem for online experiments, as it precludes person-level randomization. Randomization must instead be done using imperfect proxies for people, like cookies, email addresses or device identifiers.

By: Dominic Coey, Michael Bailey
April 11, 2016

Do Cascades Recur?

WWW 2016

Beyond a certain popularity of content, the rate of recurrence drops as cascades start exhausting the population of interested individuals. We reproduce these observed patterns in a simple model of content recurrence simulated on a real social network.

By: Justin Cheng, Lada Adamic, Jon Kleinberg, Jure Leskovec
April 11, 2016

Discovery of Topical Authorities in Instagram

WWW 2016

In this paper, we present a novel approach that we call the Authority Learning Framework (ALF) to find topical authorities in Instagram.

By: Aditya Pal, Amaç Herdağdelen, Sourav Chatterji, Sumit Taank, Deepayan Chakrabarti
March 23, 2016

Social Networks and Housing Markets

SSRN

We document that the recent house price experiences within an individual’s social network affect her perceptions of the attractiveness of property investments, and through this channel have large effects on her housing market activity.

By: Michael Bailey, Ruiqing Cao, Theresa Kuchler, Johannes Stroebel
March 15, 2016

Social Hash: an Assignment Framework for Optimizing Distributed Systems Operations on Social Networks

USINEX Symposium on Networked Systems Design and Implementation (NSDI 2016)

We describe the social hash framework, which uses graph partitioning techniques to improve the performance of systems within Facebook. We highlight two applications: 1. how routing similar users to the same web cluster improves our cache performance, 2. how co-locating socially similar data on the same host improves the performance of data serving systems.

By: Alon Shalita, Brian Karrer, Igor Kabiljo, Arun Sharma, Alessandro Presta, Aaron Adcock, Herald Kllapi, Michael Stumm
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

How Blind People Interact with Visual Content on Social Networking Services

Computer-Supported Cooperative Work and Social Computing (CSCW)

In this paper, we explore blind people’s motivations, challenges, interactions, and experiences with visual content on Social Networking Services (SNSs). We present findings from an interview study of 11 individuals and a survey study of 60 individuals, all with little to no functional vision.

By: Violeta Voykinska, Shiri Azenkot, Shaomei Wu, Gilly Leshed
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

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