Paper: Tweet Recommendation with Graph Co-Ranking

ACL ID P12-1054
Title Tweet Recommendation with Graph Co-Ranking
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2012

As one of the most popular micro-blogging services, Twitter attracts millions of users, producing millions of tweets daily. Shared in- formation through this service spreads faster than would have been possible with tradi- tional sources, however the proliferation of user-generation content poses challenges to browsing and finding valuable information. In this paper we propose a graph-theoretic model for tweet recommendation that presents users with items they may have an interest in. Our model ranks tweets and their authors simulta- neously using several networks: the social net- work connecting the users, the network con- necting the tweets, and a third network that ties the two together. Tweet and author entities are ranked following a co-ranking algorithm based on the intuition that th...