Research Area
Year Published

653 Results

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.

By: Lars Backstrom, Eric Sun, Cameron Marlow

April 19, 2010

ePluribus: Ethnicity on Social Networks

AAAI CONFERENCE ON WEBLOGS AND SOCIAL MEDIA (ICWSM)

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.

By: 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…

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

February 1, 2010

Social Network Activity and Social Well-Being

ACM Conference on Human Factors in Computing Systems (CHI)

Previous research has shown a relationship between use of social networking sites and feelings of social capital. However, most studies have relied on self-reports by college students. The goals of the current study are to (1) validate the common self-report scale using empirical data from Facebook, (2) test whether previous findings generalize to older and international populations, and (3) delve into the specific activities linked to feelings of social capital and loneliness.

By: Moira Burke, Cameron Marlow, Thomas Lento

February 1, 2010

An Unobtrusive Behavioral Model of “Gross National Happiness”

ACM Conference on Human Factors in Computing Systems (CHI)

I analyze the use of emotion words for approximately 100 million Facebook users since September of 2007. “Gross national happiness” is operationalized as a standardized difference between the use of p…

By: Adam D. I. Kramer

August 1, 2009

Hive – A Warehousing Solution Over a Map-Reduce Framework

International Conference on Very Large Data Bases (VLDB)

The size of data sets being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hadoop is a popular o…

By: Ashish Thusoo, Joydeep Sen Sarma, Namit Jain, Zheng Shao, Prasad Chakka, Suresh Antony, Hao Liu, Pete Wyckoff

June 1, 2009

Feed Me: Motivating Newcomer Contribution in Social Network Sites

ACM Conference on Human Factors in Computing Systems

Social networking sites (SNS) are only as good as the content their users share. Therefore, designers of SNS seek to improve the overall user experience by encouraging members to contribute more content. However, user motivations for contribution in SNS are not well understood. This is particularly true for newcomers, who may not recognize the value of contribution. Using server log data from approximately 140,000 newcomers in Facebook, we predict long-term sharing based on the experiences the newcomers have in their first two weeks. We test four mechanisms: social learning, singling out, feedback, and distribution.

By: Moira Burke, Cameron Marlow, Thomas Lento

April 1, 2009

Gesundheit! Modeling Contagion through Facebook News Feed

AAAI Conference on Weblogs and Social Media

Whether they are modeling bookmarking behavior in Flickr or cascades of failure in large networks, models of diffusion often start with the assumption that a few nodes start long chain reactions, resulting in large-scale cascades.

By: Eric Sun, Itamar Rosenn, Cameron Marlow, Thomas Lento

September 8, 2017

Deal or No Deal? End-to-End Learning for Negotiation Dialogues

Conference on Empirical Methods on Natural Language Processing (EMNLP)

Negotiations require complex communication and reasoning skills, but success is easy to measure, making this an interesting task for AI. We gather a large dataset of human-human negotiations on a multi-issue bargaining task, where agents who cannot observe each other’s reward functions must reach an agreement (or a deal) via natural language dialogue. For the first time, we show it is possible to train end-to-end models for negotiation, which must learn both linguistic and reasoning skills with no annotated dialogue states.

By: Mike Lewis, Denis Yarats, Yann Dauphin, Devi Parikh, Dhruv Batra

September 27, 2017

Forecasting at Scale

The American Statistician 2017

To address the challenges of producing reliable and high-quality data science forecasts, we describe a practical approach to forecasting “at scale” that combines configurable models with analyst-in-the-loop performance analysis.

By: Sean J. Taylor, Ben Letham