The Who-To-Follow System at Twitter: Strategy, Algorithms, and Revenue Impact
References
- (2010) Fast incremental and personalized pagerank. Accessed September 3, 2014, http://www.vldb.org/pvldb/vol4/p173-bahmani.pdf.Google Scholar
- (1998) What can you do with a web in your pocket? Data Engrg. Bull. 21(2):37–47.Google Scholar
- (2009) Life on the list. Accessed August 31, 2014, http://dashes.com/anil/2009/12/life-on-the-list.html.Google Scholar
- (2008) MapReduce: Simplified data processing on large clusters. Comm. ACM 51(1):107–113.Crossref, Google Scholar
- (2013) WTF: The who to follow service at Twitter. Proc. 22nd Internat. World Wide Web Conf. (IW3C2, Geneva), 505–514.Crossref, Google Scholar
- (1999) Authoritative sources in a hyperlinked environment. J. ACM 46(5):604–632.Crossref, Google Scholar
- (2014) Quote provided via personal communication with the authors, October 16.Google Scholar
- (2014) Quote provided via personal communication with the authors, October 16.Google Scholar
- (2009) Suggested users. Accessed September 3, 2014, https://blog.twitter.com/2009/suggested-users.Google Scholar
- (2012) Twitter, the startup that wouldn’t die. Accessed September 3, 2014, http://www.businessweek.com/articles/2012-03-01/twitter-the-startup-that-wouldnt-die#p2.Google Scholar
- Twitter (2010) Discovering who to follow. Accessed August 31, 2014, https://blog.twitter.com/2010/discovering-who-follow.Google Scholar
- United States Securities and Exchange Commission (2013) Form S-1, registration statement under the securities act of 1933, filed with the securities and exchange commission on October 3. Accessed September 1, 2014, http://www.sec.gov/Archives/edgar/data/1418091/000119312513390321/d564001ds1.htm.Google Scholar
- (2013) Dimension independent similarity computation. J. Machine Learning Res. 14(1):1605–1626.Google Scholar

