Data Science

Gaining insights to deliver meaningful social interactions

Data scientists at Facebook conduct large-scale, global, quantitative research to gain deeper insights into how people interact with each other and the world around them.

Our findings directly inform decisions to improve people’s everyday experiences on Facebook, make it easier and more intuitive to use, and find ways to facilitate meaningful social interactions. Research efforts span a variety of disciplines, including computational social science, econometrics, operations research, market intelligence, survey science, and statistical computing. We employ a mixture of methods to accomplish our goals, including machine learning, field experiments, surveys, and information visualization. We also build scalable platforms for the collection, management, and analysis of data, and actively contribute our scientific findings to the academic research community.

For information about Core Data Science research at Facebook, visit the Core Data Science page.

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Latest Publications

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ACM SIGIR - July 11, 2021

From Producer Success to Retention: a New Role of Search and Recommendation Systems on Marketplaces

Viet Ha-Thuc, Matthew Wood, Yunli Liu, Jagadeesan Sundaresan

Operations Research Journal - July 1, 2021

Multiplicative Pacing Equilibria in Auction Markets

Vincent Conitzer, Christian Kroer, Eric Sodomka, Nicolas E. Stier-Moses

AISTATS - April 30, 2021

Accelerating Metropolis-Hastings with Lightweight Inference Compilation

Feynman Liang, Nimar Arora, Nazanin Tehrani, Yucen Li, Michael Tingley, Erik Meijer

Innovative Technology at the Interface of Finance and Operations - March 31, 2021

Market Equilibrium Models in Large-Scale Internet Markets

Christian Kroer, Nicolas E. Stier-Moses

Explore Data Science

 

Automatic Alt-Text (AAT) allows screen reader users the ability to understand the content of most images (hopefully all images soon!) in News Feed.

 

The reach of Facebook friendships across European cities.

 

Calculating three and a half degrees of separation.

 

Researchers explored the dynamic of jobs running in families. This network visualization shows how much more likely a child of a parent in one profession is to choose another profession vs. someone from the general population.

 

Example social network showing exposure to diverse information on Facebook

 

Visualization of popular Indian politicians and political organizations for each state and their fan following across states. Visualization inspired by mbostock’s hierarchical edge bundling.

 

Figure shows different cities in India and the most prominent emotion among the posts from that city as they celebrated Independence Day.

Core Data Science at Facebook

3:09 | April 23, 2020

Open Source Projects

1:36 | August 16, 2019

Social Connectedness Index

1:11 | July 1, 2019

Social Good Projects

1:24 | July 1, 2019

Open Research Awards

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April 21, 2021

2021 Statistics for Improving Insights, Models, and Decisions request for proposals

At Facebook, our research teams strive to improve decision making for a business that touches the lives of billions of…

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