Why do people share their context information on social network services? a qualitative study and an experimental study on users' behavior of balancing perceived benefit and risk

Haein Lee, Hyejin Park, Jinwoo Kim

Research output: Contribution to journalArticlepeer-review

123 Citations (Scopus)

Abstract

Despite the rapid growth of context-aware systems and ubiquitous computing, the factors influencing users' decision to share their context information in a social setting are poorly understood. This study aims to clarify why users share their context information in social network service (SNS), even while they are concerned with the potential risk at the same time. Drawing on the diverse theories of self- disclosure, we take an approach that the consideration of benefit encourages users to endure the existence of risk, and that users actively adjust the way they share their information to optimize the level of benefit and risk. In a qualitative study, we examined what kinds of risks and benefits exist in context information sharing situations and how users control them. An experiment was conducted using stimuli that simulate the actual use of SNS to investigate the effect of various context types and control types on users' expected benefit and risk and their intention to share. The results showed that both expected benefit and expected risk influenced users' intention to share. More interestingly, the effect of expected benefit was found to be stronger than that of expected risk. Moreover, different privacy control strategies were found to have induced different effects on the expected benefit and expected risk. Implications and limitations of this study were proposed at the end of this study.

Original languageEnglish
Pages (from-to)862-877
Number of pages16
JournalInternational Journal of Human Computer Studies
Volume71
Issue number9
DOIs
Publication statusPublished - 2013

Bibliographical note

Funding Information:
This work is supported by the National Research Foundation of Korea Grant funded by the Korean Government ( NRF-2011-0012490 ). The authors appreciate Jonathan Balkind for proof reading the article and Seseok Oh for providing language help.

All Science Journal Classification (ASJC) codes

  • Software
  • Human Factors and Ergonomics
  • Education
  • Engineering(all)
  • Human-Computer Interaction
  • Hardware and Architecture

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