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550 Results

August 11, 2013

Uncertainty in Online Experiments with Dependent Data: An Evaluation of Bootstrap Methods

ACM Conference on Knowledge Discovery and Data Mining (KDD)

Many online experiments exhibit dependence between users and items. For example, in online advertising, observations that have a user or an ad in common are likely to be associated. Because of this, even in experiments involving millions of subjects, the difference in mean outcomes between control and treatment conditions can have substantial variance. Previous theoretical and simulation results demonstrate that not accounting for this kind of dependence structure can result in confidence intervals that are too narrow, leading to inaccurate hypothesis tests.

By: Eytan Bakshy, Dean Eckles
August 11, 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?

By: Khalid El-Arini, Min Xu, Emily Fox, Carlos Guestrin
August 11, 2013

Speeding up Large-Scale Learning with a Social Prior

ACM Conference on Knowledge Discovery and Data Mining (KDD)

Slow convergence and poor initial accuracy are two problems that plague efforts to use very large feature sets in online learning. This is especially true when only a few features are ‘active’ in any…

By: Deepayan Chakrabarti, Ralf Herbrich
July 23, 2013

Semantic Hashing using Tags and Topic Modeling

ACM Special Interest Group on Information Retrieval Conference (SIGIR)

It is an important research problem to design efficient and effective solutions for large scale similarity search. One popular strategy is to represent data examples as compact binary codes through semantic hashing, which has produced promising results with fast search speed and low storage cost. Many existing semantic hashing methods generate binary codes for documents by modeling document relationships based on similarity in a keyword feature space. Two major limitations in existing methods are: (1) Tag information is often associated with documents in many real world applications, but has not been fully exploited yet; (2) The similarity in keyword feature space does not fully reflect semantic relationships that go beyond keyword matching.

By: Qifan Wang, Dan Zhang, Luo Si
July 16, 2013

Selection Effects in Online Sharing: Consequences for Peer Adoption

ACM Conference on Electronic Commerce (EC)

Most models of social contagion take peer exposure to be a corollary of adoption, yet in many settings, the visibility of one’s adoption behavior happens through a separate decision process. In online systems, product designers can define how peer exposure mechanisms work: adoption behaviors can be shared in a passive, automatic fashion, or occur through explicit, active sharing.

By: Sean J. Taylor, Eytan Bakshy, Sinan Aral
July 14, 2013

TAO: Facebook’s Distributed Data Store for the Social Graph

USENIX Annual Technical Conference 2013

We introduce a simple data model and API tailored for serving the social graph, and TAO, an implementation of this model.

By: Nathan Bronson, Zach Amsden, George Cabrera, Prasad Chakka, Peter Dimov, Hui Ding, Jack Ferris, Anthony Giardullo, Sachin Kulkarni, Harry Li, Mark Marchukov, Dmitri Petrov, Lovro Puzar, Yee Jiun Song, Venkat Venkataramani
July 9, 2013

Calling All Facebook Friends: Exploring requests for help on Facebook

AAAI Conference on Weblogs and Social Media (ICWSM)

Past research suggests Facebook use is linked to perceptions of social capital, a concept that taps into the resources people gain from interactions with their social network. In this study, we examin…

By: Nicole Ellison, Rebecca Gray, Jessica Vitak, Cliff Lampe, Andrew Tresolini Fiore
July 8, 2013

The Anatomy of Large Facebook Cascades

AAAI Conference on Weblogs and Social Media (ICWSM)

When users post photos on Facebook, they have the option of allowing their friends, followers, or anyone at all to subsequently reshare the photo. A portion of the billions of photos posted to Facebook generates cascades of reshares, enabling many additional users to see, like, comment, and reshare the photos.

By: Alex Dow, Lada Adamic, Adrien Friggeri
July 8, 2013

Families on Facebook

AAAI Conference on Weblogs and Social Media (ICWSM)

This descriptive study of millions of US Facebook users documents “friending” and communication patterns, exploring parent-child relationships across a variety of life stages and gender combinations.

By: Moira Burke, Lada Adamic, Karyn Marciniak
July 2, 2013

Self-censorship on Facebook

AAAI Conference on Weblogs and Social Media (ICWSM)

We report results from an exploratory analysis examining “last-minute” self-censorship, or content that is filtered after being written, on Facebook. We collected data from 3.9 mil-lion users over 17 days and associate self-censorship behavior with features describing users, their social graph, and the interactions between them.AAAI Conference on Weblogs and Social Media (ICWSM)

By: Sauvik Das, Adam D. I. Kramer