From chatter to headlines: Harnessing the real-time web for personalized news recommendation

Gianmarco De Francisci Morales, Aristides Gionis, Claudio Lucchese

Research output: Chapter in Book/Report/Conference proceedingConference contribution

83 Citations (Scopus)

Abstract

We propose a new methodology for recommending interesting news to users by exploiting the information in their twitter persona. We model relevance between users and news articles using a mix of signals drawn from the news stream and from twitter: the profile of the social neighborhood of the users, the content of their own tweet stream, and topic popularity in the news and in the whole twitter-land. We validate our approach on a real-world dataset of approximately 40k articles coming from Yahoo! News and one month of crawled twitter data. We train our model using a learning-to-rank approach and support-vector machines. The train and test set are drawn from Yahoo! toolbar log data. We heuristically identify 3 214 users of twitter in the log and use their clicks on news articles to train our system. Our methodology is able to predict with good accuracy the news articles clicked by the users and rank them higher than other news articles. The results show that the combination of various signals from real-time web and microblogging platforms can be a useful resource to understand user behavior.

Original languageEnglish
Title of host publicationWSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining
Pages153-162
Number of pages10
DOIs
Publication statusPublished - 15 Mar 2012
Event5th ACM International Conference on Web Search and Data Mining, WSDM 2012 - Seattle, WA, United States
Duration: 8 Feb 201212 Feb 2012

Publication series

NameWSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining

Other

Other5th ACM International Conference on Web Search and Data Mining, WSDM 2012
CountryUnited States
CitySeattle, WA
Period8/2/1212/2/12

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Keywords

  • Micro-blogging applications
  • News recommendation
  • Personalization
  • Real-time web
  • Recommendation systems

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

De Francisci Morales, G., Gionis, A., & Lucchese, C. (2012). From chatter to headlines: Harnessing the real-time web for personalized news recommendation. In WSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining (pp. 153-162). (WSDM 2012 - Proceedings of the 5th ACM International Conference on Web Search and Data Mining). https://doi.org/10.1145/2124295.2124315