Privacy Threats and Protection Recommendations for the Use of Geosocial Network Data in Research

O. Kounadi (Corresponding Author), Bernd Resch, Andreas Petutschnig

Research output: Contribution to journalArticleAcademicpeer-review

12 Citations (Scopus)
93 Downloads (Pure)


Inference attacks and protection measures are two sides of the same coin. Although the former aims to reveal information while the latter aims to hide it, they both increase awareness regarding the risks and threats from social media apps. On the one hand, inference attack studies explore the types of personal information that can be revealed and the methods used to extract it. An additional risk is that geosocial media data are collected massively for research purposes, and the processing or publication of these data may further compromise individual privacy. On the other hand, consistent and increasing research on location protection measures promises solutions that mitigate disclosure risks. In this paper, we examine recent research efforts on the spectrum of privacy issues related to geosocial network data and identify the contributions and limitations of these research efforts. Furthermore, we provide protection recommendations to researchers that share, anonymise, and store social media data or publish scientific results.

Original languageEnglish
Article number191
Pages (from-to)1-17
Number of pages17
JournalSocial Sciences
Issue number10
Publication statusPublished - 11 Oct 2018


  • Privacy
  • Geoprivacy
  • Geosocial network data
  • Anonymisation
  • Location-based social networks

Cite this