Common neighbour similarity-based approach to support intimacy measurement in social networks

Kwangsoo Seol, Jeong Dong Kim, Doo Kwon Baik

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

A large amount of social data is being generated every day, as the Internet becomes more pervasive and mobile devices more ubiquitous. Accordingly, Internet users often experience difficulty finding the content they want, resulting in the popularity of personalized services that provide user-customized content. Intimacy between users of social network services can be utilized as a foundational technology for personalized services. In this paper, an intimacy measurement method for social networking services based on common neighbour similarity is proposed. The proposed method uses the link relationship between users for intimacy measurements and can be applied to general users. Further, it promotes easy data collection using publicly available data. To evaluate the proposed intimacy measurement method experimentally, a significant amount of user data was collected from Twitter. In addition, various statistical datasets were presented, and regression analyses conducted on graphs extracted from user data were collected to interpret the meaning of the intimacy index measured using the proposed method with existing social networking services.

Original languageEnglish
Pages (from-to)128-137
Number of pages10
JournalJournal of Information Science
Volume42
Issue number2
DOIs
Publication statusPublished - 2016 Apr 1

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intimacy
social network
Internet
measurement method
Mobile devices
networking
social data
twitter
popularity
regression
experience

Keywords

  • common neighbour similarity
  • intimacy measurement
  • social data analysis
  • social networking service

ASJC Scopus subject areas

  • Information Systems
  • Library and Information Sciences

Cite this

Common neighbour similarity-based approach to support intimacy measurement in social networks. / Seol, Kwangsoo; Kim, Jeong Dong; Baik, Doo Kwon.

In: Journal of Information Science, Vol. 42, No. 2, 01.04.2016, p. 128-137.

Research output: Contribution to journalArticle

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