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102 Results

May 13, 2013

CopyCatch: Stopping Group Attacks by Spotting Lockstep Behavior in Social Networks

International World Wide Web Conference (WWW)

In this paper we focus on the social network Facebook and the problem of discerning ill-gotten Page Likes, made by spammers hoping to turn a profit, from legitimate Page Likes. Our method, which we refer to as CopyCatch, detects lockstep Page Like patterns on Facebook by analyzing only the social graph between users and Pages and the times at which the edges in the graph (the Likes) were created.

By: Alex Beutel, Tom Wanhong Xu, Venkatesan Guruswami, Christopher Palow, Christos Faloutsos
May 13, 2013

Subgraph Frequencies: Mapping the Empirical and Extremal Geography of Large Graph Collections

International World Wide Web Conference (WWW)

A growing set of on-line applications are generating data that can be viewed as very large collections of small, dense social graphs – these range from sets of social groups, events, or collaboration projects to the vast collection of graph neighborhoods in large social networks.

By: Johan Ugander, Lars Backstrom, Jon Kleinberg
April 27, 2013

Gender, Topic, and Audience Response: An Analysis of User-Generated Content on Facebook

ACM Conference on Human Factors in Computing Systems (CHI)

Although users generate a large volume of text on Facebook every day, we know little about the topics they choose to talk about, and how their network responds. Using Latent Dirichlet Allocation (LDA)…

By: Yi-Chia Wang, Moira Burke, Robert Kraut
April 27, 2013

Quantifying the Invisible Audience in Social Networks

ACM Conference on Human Factors in Computing Systems (CHI)

When you share content in an online social network, who is listening? Users have scarce information about who actually sees their content, making their audience seem invisible and difficult to estimate. However, understanding this invisible audience can impact both science and design, since perceived audiences influence content production and self-presentation online.

By: Michael Bernstein, Eytan Bakshy, Moira Burke, Brian Karrer
April 1, 2013

Using Facebook after Losing a Job: Differential Benefits of Strong and Weak Ties

ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW)

Among those who have recently lost a job, social networks in general and online ones in particular may be useful to cope with stress and find new employment. This study focuses on the psychological an…

By: Moira Burke, Robert Kraut
February 6, 2013

Characterizing and Curating Conversation Threads: Expansion, Focus, Volume, Re-entry

ACM International Conference on Web Search and Data Mining (WSDM)

Discussion threads form a central part of the experience on many Web sites, including social networking sites such as Facebook and Google Plus and knowledge creation sites such as Wikipedia.

By: Lars Backstrom, Jon Kleinberg, Lillian Lee, Cristian Danescu-Niculescu-Mizil
February 6, 2013

Arrival and Departure Dynamics in Social Networks

ACM International Conference on Web Search and Data Mining (WSDM)

In this paper, we consider the natural arrival and departure of users in a social network, and ask whether the dynamics of arrival, which have been studied in some depth, also explain the dynamics of departure, which are not as well studied.

By: Shaomei Wu, Atish Das Sarma, Alex Fabrikant, Silvio Lattanzi, Andrew Tomkins
February 6, 2013

Balanced Label Propagation for Partitioning Massive Graphs

ACM International Conference on Web Search and Data Mining (WSDM)

Partitioning graphs at scale is a key challenge for any application that involves distributing a graph across disks, machines, or data centers. Graph partitioning is a very well studied problem with a…

By: Johan Ugander, Lars Backstrom
February 5, 2013

Yahtzee: An Anonymized Group Level Matching Procedure

PLOS One

Researchers often face the problem of needing to protect the privacy of subjects while also needing to integrate data that contains personal information from diverse data sources. The advent of comput…

By: Jason J. Jones, Robert Bond, Christopher J. Fariss, Jaime Settle, Adam D. I. Kramer, Cameron Marlow
January 2, 2013

Inferring Tie Strength from Online Directed Behavior

PLOS One

Some social connections are stronger than others. People have not only friends, but also best friends. Social scientists have long recognized this characteristic of social connections and researchers frequently use the term ‘tie strength’ to refer to this concept. We used online interaction data (specifically, Facebook interactions) to successfully identify real-world strong ties.

By: Jason J. Jones, Jaime Settle, Robert Bond, Christopher J. Fariss, Cameron Marlow