An information recommendation technique based on influence and activeness of users in social networks

Minsoo Lee, Soyeon Oh

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Over the past few years, the number of users of social network services has been exponen-tially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.

Original languageEnglish
Article number2530
JournalApplied Sciences (Switzerland)
Volume11
Issue number6
DOIs
StatePublished - 2 Mar 2021

Keywords

  • Recommendation technique
  • Social network service
  • User activity
  • User influence

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