Understanding and Predicting Cyberstalking in Social Media : Integrating Theoretical Perspectives on Shame, Neutralization, Self-Control, Rational Choice, and Social Learning

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)peer-review

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Author(s)

  • Paul Benjamin LOWRY
  • Jun ZHANG
  • Chuang WANG
  • Tailai WU
  • Siponen MIKKO

Related Research Unit(s)

Detail(s)

Original languageEnglish
Publication statusPublished - 15 Dec 2013

Conference

TitleInternational Conference on Information Systems
PlaceItaly
Period15 - 18 December 2013

Abstract

Cyberstalking has received increasing attention in academia and the public for its pervasive effect on society. However, there has been little comprehensive research concerning the mechanisms of cyberstalking behavior, particularly in social media. In this article, we define cyberstalking and explain how it is dramatically different from real-world stalking, and thus calls for additional taxonomic and theoretical development. Based on an extensive review of the literature and case studies of cyberstalking, we then propose a comprehensive taxonomy of cyberstalking. On this basis, we develop a theoretical model to explain and predict cyberstalking behavior. To better understand cyberstalking, we propose a model that integrates five theories within three levels of prediction: the intrapersonal level (emotional theory, neutralization theory, and self-control theory), the situational level (rational choice theory), and the interpersonal level (social learning theory). On this taxonomic and theoretical foundation, future empirical research should be able to further explain, predict, and test cyberstalking behavior online.

Citation Format(s)

Understanding and Predicting Cyberstalking in Social Media : Integrating Theoretical Perspectives on Shame, Neutralization, Self-Control, Rational Choice, and Social Learning. / LOWRY, Paul Benjamin; ZHANG, Jun; WANG, Chuang; WU, Tailai; MIKKO, Siponen.

2013. Paper presented at International Conference on Information Systems, Italy.

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)32_Refereed conference paper (no ISBN/ISSN)peer-review