Modelling perceived risks to personal privacy from location disclosure on online social networks
| Autor: | W. B. El-Geresy, George Theodorakopoulos, Alia I. Abdelmoty, Fatma Alrayes |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Location data
Computer science business.industry media_common.quotation_subject 05 social sciences Geography Planning and Development Visibility (geometry) Internet privacy 0211 other engineering and technologies 0507 social and economic geography Face (sociological concept) 02 engineering and technology Library and Information Sciences Compliance (psychology) Informed consent Perception business 050703 geography 021101 geological & geomatics engineering Information Systems media_common |
| Zdroj: | International Journal of Geographical Information Science. 34:150-176 |
| ISSN: | 1362-3087 1365-8816 |
| DOI: | 10.1080/13658816.2019.1654109 |
| Popis: | As users increasingly rely on online social networks for their communication\ud activities, personal location data processing through\ud such networks poses significant risks to users’ privacy. Location\ud tracks can be mined with other shared information to extract rich\ud personal profiles. To protect users’ privacy, online social networks\ud face the challenge of ensuring transparent communication to\ud users of how their data are processed, and explicitly obtaining\ud users’ informed consent for the use of this data. In this paper, we\ud explore the complex nature of the location disclosure problem and\ud its risks to personal privacy. We evaluate, with an experiment\ud involving 715 participants, the contributing factors to the perception\ud of such risks with scenarios that mimic (a) realistic modes of\ud interaction, where users are not fully aware of the extent of their\ud location-related data being processed, and (b) with devised scenarios\ud that deliberately inform users of the data they are sharing\ud and its visibility to others. The results are used to represent the\ud users’ perception of privacy risks when sharing their location\ud information online and to derive a possible model of privacy\ud risks associated with this sharing behaviour. Such a model can\ud inform the design of privacy-aware online social networks to\ud improve users’ trust and to ensure compliance with legal frameworks\ud for personal privacy. |
| Databáze: | OpenAIRE |
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