Users joining multiple sites: Friendship and popularity variations across sites

Reza Zafarani, Huan Liu

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Our social media experience is no longer limited to a single site. We use different social media sites for different purposes and our information on each site is often partial. By collecting complementary information for the same individual across sites, one can better profile users. These profiles can help improve online services such as advertising or recommendation across sites. To combine complementary information across sites, it is critical to understand how information for the same individual varies across sites. In this study, we aim to understand how two fundamental properties of users vary across social media sites. First, we study how user friendship behavior varies across sites. Our findings show how friend distributions for individuals change as they join new sites. Next, we analyze how user popularity changes across sites as individuals join different sites. We evaluate our findings and demonstrate how our findings can be employed to predict how popular users are likely to be on new sites they join.

Original languageEnglish (US)
Pages (from-to)83-89
Number of pages7
JournalInformation Fusion
Volume28
DOIs
StatePublished - Mar 1 2016

Keywords

  • Cross-media study
  • Cross-site information fusion
  • Cross-site user analysis
  • Friendship analysis
  • Popularity analysis

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Hardware and Architecture
  • Information Systems

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