Privacy Threats and Protection Recommendations for the Use of Geosocial Network Data in Research
Bibliographic Data
| ID | 5934586 |
|---|---|
| Authors | Ourania Kounadi (0000-0002-5998-7343, University of Salzburg, corresponding author), Bernd Resch (0000-0002-2233-6926, University of Salzburg), Andreas Petutschnig (0000-0001-5029-2425, University of Salzburg) |
| Year | 2018 |
| Volume | 7 |
| Issue | 10 |
| Pages | 191 |
| Publication date | 2018-10-11 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2076-0760 • E-ISSN: 2076-0760 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/socsci7100191 |
| OpenAlex | W2897100129 |
| Language | EN |
| Citations received | 15 |
| References cited | 71 |
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
Advertising · Business · Compromise · Computer security · Data Protection Act 1998 · Data science · Inference · Information sensitivity · Internet privacy · Personally identifiable information · Political science · Privacy Protection · Publication · Social media · World Wide Web · Computer Science · Data-Driven Disease Surveillance · Privacy-Preserving Technologies in Data · Privacy, Security, and Data Protection
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An exploratory assessment of the effectiveness of geomasking methods on privacy protection and analytical accuracy for individual-level geospatial data
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The impact of using social media data in crime rate calculations
| Unique citing works | 15 |
|---|---|
| Citations per year | 2,14 |
| Citation span | 2019 - 2025 (7) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 15 |