Back
Document
Research report

Exploring nuances of user privacy preferences on a platform for political participation

    30.11.2017

10

User Privacy Preferences
Fuzzy Clustering
Data Analysis
English A problematic gap between existing online privacy controls and actual user disclosure behavior motivates researchers to focus on a design and development of intelligent privacy controls. These intelligent controls intend to decrease the burden of privacy decision-making and generate user-tailored privacy suggestions. To do so, at first it is necessary to analyze user privacy preferences. Previous studies have shown that user privacy profiles tend to have a multidimensional structure, which in turn might bring issues of an inexact user classification. This paper proposes to apply a fuzzy clustering approach, where fuzzy membership degree values can be used for the calculation of more precise personalized privacy suggestions. Based on the real-world dataset collected from a political platform 1, the fuzzy c-means algorithm was applied to demonstrate the multidimensionality and the existence of imprecise user privacy profiles, where a user simultaneously possesses features inherent in several clusters.
Collections
Faculty
Faculté des sciences économiques et sociales et du management
Department
Département d'informatique
Language
  • English
Classification
Computer science and technology
Other electronic version

Faculté SES

Series statement
  • Internal working papers / DIUF ; 17-02
License
License undefined
Identifiers
  • RERO DOC 305946
  • RERO R008738080
Persistent URL
https://folia.unifr.ch/unifr/documents/305975
Statistics
Document views: 70 File downloads:
  • IWP17_02_diuf.pdf: 74