Research Area
Year Published

121 Results

June 28, 2018

Hardware Remediation At Scale

International Conference on Dependable Systems and Networks (DSN)

Large scale services have automated hardware remediation to maintain the infrastructure availability at a healthy level. In this paper, we share the current remediation flow at Facebook, and how it is being monitored.

By: Fan (Fred) Lin, Matt Beadon, Harish Dattatraya Dixit, Gautham Vunnam, Amol Desai, Sriram Sankar

June 25, 2018

Do Diffusion Protocols Govern Cascade Growth?

International AAAI Conference on Web and Social Media (ICWSM)

Large cascades can develop in online social networks as people share information with one another. Though simple reshare cascades have been studied extensively, the full range of cascading behaviors on social media is much more diverse. Here we study how diffusion protocols, or the social exchanges that enable information transmission, affect cascade growth, analogous to the way communication protocols define how information is transmitted from one point to another.

By: Justin Cheng, Jon Kleinberg, Jure Leskovec, David Liben-Nowell, Bogdan State, Karthik Subbian, Lada Adamic

June 25, 2018

“I’m Never Happy with What I Write”: Challenges and Strategies of People with Dyslexia on Social Media

International Conference on Web and Social Media

This work studies the experiences, challenges, and strategies of people with dyslexia when using social media. We interviewed 11 people with dyslexia to understand their general experiences with reading and writing content on Facebook. The interview study findings highlight the challenges they face when writing content on Social Networking Sites (SNSs), and their strategies for mitigating these challenges.

By: Lindsay Reynolds, Shaomei Wu

June 3, 2018

Interaction Content Aware Network Embedding via Co-embedding of Nodes and Edges

Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)

Network embedding has been increasingly employed in network analysis as it can learn node representations that encode the network structure resulting from node interactions. In this paper, besides the network structure, the interaction content within which each interaction arises is also embedded because it reveals interaction preferences of the two nodes involved, and interaction preferences are essential characteristics that nodes expose in the network environment.

By: Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu

April 21, 2018

A Face Recognition Application for People with Visual Impairments: Understanding Use Beyond the Lab

Conference on Human Factors in Computing Systems (CHI)

We present Accessibility Bot, a research prototype bot on Facebook Messenger, which leverages state-of-the-art computer vision algorithms and the existing set of tagged photos of a user’s friends on Facebook to help people with visually impairments recognize their friends.

By: Yuhang Zhao, Shaomei Wu, Lindsay Reynolds, Shiri Azenkot

December 15, 2017

Mapping the world population one building at a time

ArXive

Here, we present a computer vision method based on machine learning to create population maps from satellite imagery at a global scale, with a spatial sensitivity corresponding to individual buildings and suitable for global deployment.

By: Tobias Tiecke, Xianming Liu, Amy Zhang, Andreas Gros, Nan Li, Gregory Yetman, Talip Kilic, Siobhan Murray

December 10, 2017

Social Structure and Trust in Massive Digital Markets

International Conference on Information Systems (ICIS)

In this paper we measure the extent to which situating transactions in networks can generate trust in online marketplaces with an empirical approach that provides external validity while eliminating many potential confounds.

By: David Holtz, Diana Lynn MacLean, Sinan Aral

August 28, 2017

Social Hash Partitioner: A Scalable Distributed Hypergraph Partitioner

Very Large Data Bases Conference (VLDB)

We design and implement a distributed algorithm for balanced k-way hypergraph partitioning that minimizes fanout, a fundamental hypergraph quantity also known as the communication volume and (k − 1)-cut metric, by optimizing a novel objective called probabilistic fanout. This choice allows a simple local search heuristic to achieve comparable solution quality to the best existing hypergraph partitioners.

By: Igor Kabiljo, Brian Karrer, Mayank Pundir, Sergey Pupyrev, Alon Shalita

July 24, 2017

Untagging on Social Media: Who Untags, What do they Untag, and Why?

Journal: Computers in Human Behavior

Using de-identified, aggregated behavioral data from Facebook and a survey of 802 people, this paper aims to explore untagging by asking whether untagging occurs similarly to other self-presentation behavior and how people view this strategy.

By: Jeremy Birnholt, Moira Burke, Annie Steele

July 10, 2017

House Price Beliefs and Mortgage Leverage Choice

National Bureau of Economic Researcher (NBER)

We study the the relationship between homebuyers’ beliefs about future house price changes and their mortgage leverage choices.

By: Michael Bailey, Eduardo Dávila, Theresa Kuchler, Johannes Stroebel