July 24, 2011

Learning Relevance from a Heterogeneous Social Network and Its Application in Online Targeting

ACM Special Interest Group on Information Retrieval (SIGIR)

The rise of social networking services in recent years presents new research challenges for matching users with interesting content. While the content-rich nature of these social networks offers many…

Chi Wang, Rajat Raina, David Fong, Ding Zhou, Jiawei Han, Greg Badros
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
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.

Jonathan Chang, Eric Sun
July 1, 2011

Many-core key-value store

International Green Computing Conference (IGCC)

Scaling data centers to handle task-parallel workloads requires balancing the cost of hardware, operations, and power. Low-power, low-core-count servers reduce costs in one of these dimensions, but may require additional nodes to provide the required quality of service or increase costs by underutilizing memory and other resources.

Mateusz Berezecki, Eitan Frachtenberg, Michael Paleczny, Ken Steele
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.

Rubao Lee, Tian Luo, Yin Huai, Fusheng Wang, Yongqiang He, Xiaodong Zhang
June 12, 2011

Apache Hadoop goes realtime at Facebook

ACM Special Interest Group on Management of Data (SIGMOD)

Facebook recently deployed Facebook Messages, its first ever user-facing application built on the Apache Hadoop platform. Apache HBase is a database-like layer built on Hadoop designed to support billions of messages per day.

Dhruba Borthakur, Joydeep Sen Sarma, Jonathan Gray, Kannan Muthukkaruppan, Nicolas Spiegelberg, Hairong Kuang, Karthik Ranganathan, Dmytro Molkov, Aravind Menon, Sam Rash, Rodrigo Schmidt, Amitanand Aiyer
April 10, 2011

Facebook Immune System

Workshop on Social Network Systems (SNS)

Popular Internet sites are under attack all the time from phishers, fraudsters, and spammers. They aim to steal user information and expose users to unwanted spam. The attackers have vast resources at their disposal. They are well-funded, with full-time skilled labor, control over compromised and infected accounts, and access to global botnets.

Tao Stein, Roger Chen, Karan Mangla
March 30, 2011

FATE and DESTINI: A Framework for Cloud Recovery Testing

USENIX Symposium on Networked Systems Design and Implementation (NSDI)

As the cloud era begins and failures become commonplace, the fate and destiny of availability, reliability and performance are in the hands of failure recovery. Unfortunately, recovery problems still take place, causing downtimes, data loss, and many other problems.

Haryadi S. Gunawi, Thanh Do, Pallavi Joshi, Peter Alvaro, Joseph M. Hellerstein, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau, Koushik Sen, Dhruba Borthakur
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.

Moira Burke, Robert Kraut, Cameron Marlow
January 1, 2011

RCFile: A Fast and Space-efficient Data Placement Structure in MapReduce-based Warehouse Systems

IEEE International Conference on Data Engineering (ICDE)

MapReduce-based data warehouse systems are playing important roles of supporting big data analytics to understand quickly the dynamics of user behavior trends and their needs in typical Web service providers and social network sites (e.g., Facebook). In such a system, the data placement structure is a critical factor that can affect the warehouse performance in a fundamental way.

Yongqiang He, Rubao Lee, Yin Huai, Zheng Shao, Namit Jain, Xiaodong Zhang, Zhiwei Xu
January 1, 2011

Supervised Random Walks: Predicting and Recommending Links in Social Networks

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

Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interactions among existing members are likely to occur in the near future or which existing interactions are we missing. Although this problem has been extensively studied, the challenge of how to effectively combine the information from the network structure with rich node and edge attribute data remains largely open.

Lars Backstrom, Jure Leskovec
January 1, 2011

Network Bucket Testing

International World Wide Web Conference (WWW)

Bucket testing, also known as A/B testing, is a practice that is widely used by on-line sites with large audiences: in a simple version of the methodology, one evaluates a new feature on the site by e…

Lars Backstrom, Jure Leskovec
October 4, 2010

Finding a needle in Haystack: Facebook’s photo storage

USENIX Symposium on Operating Systems Design and Implementation (OSDI)

This paper describes Haystack, an object storage system optimized for Facebook’s Photos application. Facebook currently stores over 260 billion images, which translates to over 20 petabytes of data. U…

Doug Beaver, Sanjeev Kumar, Harry Li, Jason Sobel, Peter Vajgel
June 6, 2010

Data warehousing and analytics infrastructure at Facebook.

Special Interest Group on Management of Data (SIGMOD)

Scalable analysis on large data sets has been core to the functions of a number of teams at Facebook – both engineering and non-engineering. Apart from ad hoc analysis of data and creation of business intelligence dashboards by analysts across the company, a number of Facebook’s site features are also based on analyzing large data sets.

Ashish Thusoo, Dhruba Borthakur, Raghotham Murthy, Zheng Shao, Namit Jain, Hao Liu, Suresh Antony, Joydeep Sen Sarma
June 1, 2010

Not-so-latent dirichlet allocation: collapsed Gibbs sampling using human judgments

Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)

Probabilistic topic models are a popular tool for the unsupervised analysis of text, providing both a predictive model of future text and a latent topic representation of the corpus. Recent studies have found that while there are suggestive connections between topic models and the way humans interpret data, these two often disagree.

Jonathan Chang
June 1, 2010

Tools for Collecting Speech Corpora via Mechanical Turk

NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk

To rapidly port speech applications to new languages one of the most difficult tasks is the initial collection of sufficient speech corpora.

Ian Lane, Alex Waibel, Matthias Eck, Kay Rottmann
April 26, 2010

Find Me If You Can: Improving Geographical Prediction with Social and Spatial Proximity

International World Wide Web Conference (WWW)

Geography and social relationships are inextricably intertwined; the people we interact with on a daily basis almost always live near us. As people spend more time online, data regarding these two dimensions — geography and social relationships — are becoming increasingly precise, allowing us to build reliable models to describe their interaction. These models have important implications in the design of location-based services, security intrusion detection, and social media supporting local communities.

Lars Backstrom, Eric Sun, Cameron Marlow
April 19, 2010

ePluribus: Ethnicity on Social Networks


We propose an approach to determine the ethnic break-down of a population based solely on people’s names and data provided by the U.S. Census Bureau. We demonstrate that our approach is able to predict the ethnicities of individuals as well as the ethnicity of an entire population better than natural alternatives.

Jonathan Chang, Itamar Rosenn, Lars Backstrom, Cameron Marlow
April 13, 2010

Job Scheduling for Multi-User MapReduce Clusters

ACM European Conference on Computer Systems (EUROSYS)

Sharing a MapReduce cluster between users is attractive because it enables statistical multiplexing (lowering costs) and allows users to share a common large data set. However, we find that traditiona…

Matei Zaharia, Dhruba Borthakur, Joydeep Sen Sarma, Khaled Elmeleegy, Scott Shenker, Ion Stoica