June 7, 2013

Representing Documents Through Their Readers

ACM Conference on Knowledge Discovery and Data Mining (KDD)

From Twitter to Facebook to Reddit, users have become accustomed to sharing the articles they read with friends or followers on their social networks. While previous work has modeled what these shared stories say about the user who shares them, the converse question remains unexplored: what can we learn about an article from the identities of its likely readers?

Khalid El-Arini, Min Xu, Emily Fox, Carlos Guestrin
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.

Johan Ugander, Lars Backstrom, Jon Kleinberg
May 8, 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.

Alex Beutel, Tom Wanhong Xu, Venkatesan Guruswami, Christopher Palow, Christos Faloutsos
April 29, 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.

Michael Bernstein, Eytan Bakshy, Moira Burke, Brian Karrer
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)…

Yi-Chia Wang, Moira Burke, Robert Kraut
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…

Moira Burke, Robert Kraut
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.

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…

Johan Ugander, Lars Backstrom
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.

Lars Backstrom, Jon Kleinberg, Lillian Lee, Cristian Danescu-Niculescu-Mizil
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…

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.

Jason J. Jones, Jaime Settle, Robert Bond, Christopher J. Fariss, Cameron Marlow
September 13, 2012

A 61-million-person experiment in social influence and political mobilization

Nature

Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies, and it is unknown whether online social ne…

Robert Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime Settle
June 22, 2012

Four Degrees of Separation

ACM Web Science Conference (WebSci)

Frigyes Karinthy, in his 1929 short story “Lancszemek” (in English, “Chains”) suggested that any two persons are distanced by at most six friendship links. Stanley Milgram in his famous experiments challenged people to route postcards to a fixed recipient by passing them only through direct acquaintances. Milgram found that the average number of intermediaries on the path of the postcards lay between 4.4 and 5.7, depending on the sample of people chosen.

Lars Backstrom, Paolo Boldi, Marco Rosa, Johan Ugander, Sebastiano Vigna
June 8, 2012

Social Influence in Social Advertising: Evidence from Field Experiments

ACM Conference on Electronic Commerce (EC)

Social advertising uses information about consumers’ peers, including peer affiliations with a brand, product, organization, etc., to target ads and contextualize their display. This approach can incr…

Eytan Bakshy, Dean Eckles, Rong Yan, Itamar Rosenn
May 16, 2012

The spread of emotion via Facebook

ACM Conference on Human Factors in Computing Systems (CHI)

In this paper we study large-scale emotional contagion through an examination of Facebook status updates. After a user makes a status update with emotional content, their friends are significantly more likely to make a valence-consistent post.

Adam D. I. Kramer
April 17, 2012

Structural Diversity in Social Contagion

Proceedings of the National Academy of Sciences (PNAS)

The concept of contagion has steadily expanded from its original grounding in epidemic disease to describe a vast array of processes that spread across networks, notably social phenomena such as fads,…

Johan Ugander, Lars Backstrom, Cameron Marlow, Jon Kleinberg
April 16, 2012

The Role of Social Networks in Information Diffusion

International World Wide Web Conference (WWW)

Online social networking technologies enable individuals to simultaneously share information with any number of peers. Quantifying the causal effect of these mediums on the dissemination of informatio…

Eytan Bakshy, Itamar Rosenn, Cameron Marlow, Lada Adamic
March 1, 2012

Bootstrapping Data Arrays of Arbitrary Order

The Annals of Applied Statistics (AOAS)

In this paper we study a bootstrap strategy for estimating the variance of a mean taken over large multifactor crossed random effects data sets. We apply bootstrap reweighting independently to the lev…

Art B. Owen, Dean Eckles
July 21, 2011

Dimensions of Self-Expression in Facebook Status Updates

AAAI International Conference on Weblogs and Social Media (ICWSM)

We describe the dimensions along which Facebook users tend to express themselves via status updates using the semi-automated text analysis approach, the Meaning Extraction Method (MEM).

Adam D. I. Kramer, Cindy K. Chung
July 7, 2011

Center of Attention: How Facebook Users Allocate Attention across Friends

AAAI International Conference on Weblogs and Social Media (ICWSM)

An individual’s personal network — their set of social contacts — is a basic object of study in sociology. Studies of personal networks have focused on their size (the number of contacts) and their composition (in terms of categories such as kin and co-workers). Here we propose a new measure for the analysis of personal networks, based on the way in which an individual divides his or her attention across contacts. This allows us to contrast people who focus a large fraction of their interactions on a small set of close friends with people who disperse their attention more widely.

Lars Backstrom, Eytan Bakshy, Jon Kleinberg, Thomas Lento, Itamar Rosenn