Personalized activity streams: Sifting through the "river of news"

Ido Guy, Inbal Ronen, Ariel Raviv

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

33 Scopus citations

Abstract

Activity streams have emerged as a means to syndicate updates about a user or a group of users within a social network site or a set of sites. As the flood of updates becomes highly intensive and noisy, users are faced with a "needle in a haystack" challenge when they wish to read the news most interesting to them. In this work, we study activity stream personalization as a means of coping with this challenge. We experiment with an enterprise activity stream that includes status updates and news across a variety of social media applications. We examine an entity-based user profile and a stream-based profile across three dimensions: people, terms, and places, and provide a rich set of results through a user study that combines direct rating of the objects in the profile with rating of the news items it produces.

Original languageEnglish
Title of host publicationRecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems
Pages181-188
Number of pages8
DOIs
StatePublished - 6 Dec 2011
Externally publishedYes
Event5th ACM Conference on Recommender Systems, RecSys 2011 - Chicago, IL, United States
Duration: 23 Oct 201127 Oct 2011

Publication series

NameRecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems

Conference

Conference5th ACM Conference on Recommender Systems, RecSys 2011
Country/TerritoryUnited States
CityChicago, IL
Period23/10/1127/10/11

Keywords

  • activity streams
  • news feed
  • personalization
  • real-time web
  • recommender systems
  • social media
  • social networks
  • social streams
  • Twitter

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