The Who-To-Follow System at Twitter: Strategy, Algorithms, and Revenue Impact

Ashish Goel (), Pankaj Gupta (), John Sirois (), Dong Wang (), Aneesh Sharma () and Siva Gurumurthy ()
Additional contact information
Ashish Goel: Stanford University, Stanford, California 94035
Pankaj Gupta: Twitter Inc., San Francisco, California 94103
John Sirois: Twitter Inc., San Francisco, California 94103
Dong Wang: Twitter Inc., San Francisco, California 94103
Aneesh Sharma: Twitter Inc., San Francisco, California 94103
Siva Gurumurthy: Twitter Inc., San Francisco, California 94103

Interfaces, 2015, vol. 45, issue 1, 98-107

Abstract: The who-to-follow system at Twitter is an algorithmic data product that recommends accounts for Twitter users to follow. Building the system involved algorithmic, analytics, operational, and experimental challenges; operations research and analytics techniques played a key role in resolving these challenges. This product has had significant direct impact on Twitter’s growth and the quality of its user engagement, and has also been a major driver of revenue. More than one-eighth of all new connections on the Twitter network are a direct result of this system, and a substantial majority of Twitter’s revenue comes from its promoted products, for which this system was a foundation. To place this contribution into perspective, Twitter is now a publicly traded company with a market capitalization of more than $30 billion, projected annual revenue of close to $1 billion, and more than 240 million active users.

Keywords: computational analysis; optimization; data mining; Internet (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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