Purpose
User profiling with big data raises significant issues regarding privacy. Privacy studies typically focus on individual privacy; however, in the era of big data analytics, users are also targeted as members of specific groups, thus challenging their collective privacy with unidentified implications. Overall, this paper aims to argue that in the age of big data, there is a need to consider the collective aspects of privacy as well and to develop new ways of calculating privacy risks and identify privacy threats that emerge.
Design/methodology/approach
Focusing on a collective level, the authors conducted an extensive literature review related to information privacy and concepts of social identity. They also examined numerous automated data-driven profiling techniques analyzing at the same time the involved privacy issues for groups.
Findings
This paper identifies privacy threats for collective entities that stem from data-driven profiling, and it argues that privacy-preserving mechanisms are required to protect the privacy interests of groups as entities, independently of the interests of their individual members. Moreover, this paper concludes that collective privacy threats may be different from threats for individuals when they are not members of a group.
Originality/value
Although research evidence indicates that in the age of big data privacy as a collective issue is becoming increasingly important, the pluralist character of privacy has not yet been adequately explored. This paper contributes to filling this gap and provides new insights with regard to threats for group privacy and their impact on collective entities and society.
Big Data and Individual Privacy in the Age of the Internet of Things