Social media-driven news personalization

Shawn O'Banion*, Lawrence A Birnbaum, Kristian J Hammond

*Corresponding author for this work

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

14 Citations (Scopus)

Abstract

While social media have achieved significant and widespread adoption as platforms for sharing information, their use as a source of data for predicting user interests has not yet been fully explored. In this paper, we present a content-based approach to modeling user interests based on Twitter. Our recommendation system uses information retrieval techniques to represent tweets and users as collections of news topics, including high-level categories (e.g., sports, politics, business) and detailed subtopics (e.g., Chicago Bulls, Mitt Romney, entrepreneurship). We discuss the design of a system that uses this information to deliver news recommendations in the form of a personalized newspaper. Finally, we describe a novel method for evaluating recommendation sys- tems based on Twitter that involves mining Twitter data to identify explicit indicators of news interests and comparing these to retroactive system recommendations.

Original languageEnglish (US)
Title of host publicationRSWeb'12 - Proceedings of the 4th ACM RecSys Workshop on Recommender Systems and the Social Web
Pages45-51
Number of pages7
DOIs
StatePublished - Oct 19 2012
Event4th ACM RecSys Workshop on Recommender Systems and the Social Web, RSWeb 2012 - Dublin, Ireland
Duration: Sep 9 2012Sep 9 2012

Other

Other4th ACM RecSys Workshop on Recommender Systems and the Social Web, RSWeb 2012
CountryIreland
CityDublin
Period9/9/129/9/12

Fingerprint

Recommender systems
Information use
Sports
Information retrieval
Data mining
Industry

Keywords

  • Information retrieval
  • Personalization
  • Recom- mendation system
  • Social media analysis
  • User profiling

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

O'Banion, S., Birnbaum, L. A., & Hammond, K. J. (2012). Social media-driven news personalization. In RSWeb'12 - Proceedings of the 4th ACM RecSys Workshop on Recommender Systems and the Social Web (pp. 45-51) https://doi.org/10.1145/2365934.2365943
O'Banion, Shawn ; Birnbaum, Lawrence A ; Hammond, Kristian J. / Social media-driven news personalization. RSWeb'12 - Proceedings of the 4th ACM RecSys Workshop on Recommender Systems and the Social Web. 2012. pp. 45-51
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O'Banion, S, Birnbaum, LA & Hammond, KJ 2012, Social media-driven news personalization. in RSWeb'12 - Proceedings of the 4th ACM RecSys Workshop on Recommender Systems and the Social Web. pp. 45-51, 4th ACM RecSys Workshop on Recommender Systems and the Social Web, RSWeb 2012, Dublin, Ireland, 9/9/12. https://doi.org/10.1145/2365934.2365943

Social media-driven news personalization. / O'Banion, Shawn; Birnbaum, Lawrence A; Hammond, Kristian J.

RSWeb'12 - Proceedings of the 4th ACM RecSys Workshop on Recommender Systems and the Social Web. 2012. p. 45-51.

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

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O'Banion S, Birnbaum LA, Hammond KJ. Social media-driven news personalization. In RSWeb'12 - Proceedings of the 4th ACM RecSys Workshop on Recommender Systems and the Social Web. 2012. p. 45-51 https://doi.org/10.1145/2365934.2365943