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100 Results

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…

By: 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.

By: 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,…

By: 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…

By: 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…

By: Art B. Owen, Dean Eckles
July 17, 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.

By: Lars Backstrom, Eytan Bakshy, Jon Kleinberg, Thomas Lento, Itamar Rosenn
July 17, 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).

By: Adam D. I. Kramer, Cindy K. Chung
July 5, 2011

Location3: How Users Share and Respond to Location-Based Data on Social Networking Sites

AAAI International Conference on Weblogs and Social Media (ICWSM)

In August 2010 Facebook launched Places, a location-based service that allows users to check into points of interest and share their physical whereabouts with friends. The friends who see these events in their News Feed can then respond to these check-ins by liking or commenting on them.

By: Jonathan Chang, Eric Sun
June 20, 2011

YSmart: Yet Another SQL-to-MapReduce Translator

International Conference on Distributed Computing Systems (ICDCS)

MapReduce has become an effective approach to big data analytics in large cluster systems, where SQL-like queries play important roles to interface between users and systems. However, based on our Face book daily operation results, certain types of queries are executed at an unacceptable low speed by Hive (a production SQL-to-MapReduce translator). In this paper, we demonstrate that existing SQL-to-MapReduce translators that operate in a one-operation-to-one-job mode and do not consider query correlations cannot generate high-performance MapReduce programs for certain queries, due to the mismatch between complex SQL structures and simple MapReduce framework. We propose and develop a system called Y Smart, a correlation aware SQL-to-MapReduce translator. Y Smart applies a set of rules to use the minimal number of MapReduce jobs to execute multiple correlated operations in a complex query. Y Smart can significantly reduce redundant computations, I/O operations and network transfers compared to existing translators. We have implemented Y Smart with intensive evaluation for complex queries on two Amazon EC2 clusters and one Face book production cluster. The results show that Y Smart can outperform Hive and Pig, two widely used SQL-to-MapReduce translators, by more than four times for query execution.

By: Rubao Lee, Tian Luo, Yin Huai, Fusheng Wang, Yongqiang He, Xiaodong Zhang
February 1, 2011

Social Capital on Facebook: Differentiating Uses and Users

ACM Conference on Human Factors in Computing Systems (CHI)

Though social network site use is often treated as a monolithic activity, in which all time is equally “social” and its impact the same for all users, we examine how Facebook affects social capital depending upon: (1) types of site activities, contrasting one-on-one communication, broadcasts to wider audiences, and passive consumption of social news, and (2) individual differences among users, including social communication skill and self-esteem.

By: Moira Burke, Robert Kraut, Cameron Marlow