Managing privacy through key performance indicators when photos and videos are shared via social media

Publication Type:
Conference Proceeding
Advances in Intelligent Systems and Computing, 2019, 857, pp. 1103-1117
Issue Date:
Filename Description Size
Paper 296-Managing Privacy through Key Performance Indicators.pdfPublished version379.44 kB
Adobe PDF
Full metadata record
© Springer Nature Switzerland AG 2019. There are many definitions of privacy. What is considered sensitive varies from individual to individual. When a document is shared it may reveal certain information, the exchange of information is grounded with a specific context. This contextual grounding may not be afforded when photos and videos are shared, because they may contain rich semantic and syntactic information coded as tacit knowledge. Identifying sensitive information in a photo or a video is a major problem; therefore, rather than making assumptions about what is sensitive in a photo or a video, this research asked a group of study participants why they share content and what their concerns are (if any)? This enabled inferences to be made about categories of sensitivity in accordance with the participants’ responses. Interview data was gathered and Grounded Theory was applied. The following themes emerged from the data: a major theme, in which no privacy concerns were developed, three sub-themes in which varying levels of privacy concerns were developed and key performance indicators which manage levels of privacy were determined. This paper focuses on the main themes’ key performance indicators and how they can manage privacy when photos and videos are shared over social media.
Please use this identifier to cite or link to this item: