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

Ourania Kounadi, Bernd Resch and Andreas Petutschnig
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Ourania Kounadi: Faculty of Geo-Information Science and Earth Observation (ITC), Department of Geo-information Processing, University of Twente, 7514 AE Enschede, The Netherlands
Bernd Resch: Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria
Andreas Petutschnig: Department of Geoinformatics—Z_GIS, University of Salzburg, 5020 Salzburg, Austria

Social Sciences, 2018, vol. 7, issue 10, 1-17

Abstract: 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.

Keywords: privacy; geoprivacy; geosocial network data; location-based social networks; anonymisation (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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