Trend Analysis and Recommendation of Users’ Privacy Settings on Social Networking Services

  • Toshikazu Munemasa
  • Mizuho Iwaihara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6984)

Abstract

Social networking services (SNSs) are regarded as an indispensable social media for finding friends and interacting with them. However, their search capabilities often raise privacy concerns. Usually, an SNS provides privacy settings for each user, so that he/she can specify who can access his/her online contents. But these privacy settings often become either too simplistic or too complicated. To assist SNS users to discover their own appropriate settings, we propose a privacy-setting recommendation system, which utilizes privacy settings on public access, collected from over 66,000 real Facebook users and settings donated by participating users. We show privacy scores of the collected settings according to user categories. Our recommendation system utilizes these analysis results as well as correlations within privacy settings, and visualizes distribution of collected user’s settings. Our evaluations on test users show effectiveness of our approach.

Keywords

Item Response Theory Online Social Network Social Networking Service Privacy Setting User Category 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Toshikazu Munemasa
    • 1
  • Mizuho Iwaihara
    • 1
  1. 1.Graduate School of Information, Production and SystemsWaseda UniversityJapan

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