Taxonomy of social network data types

Abstract

Online social networks (OSNs) have become an integral part of social interaction and communication between people. Reasons include the ubiquity of OSNs that is offered through mobile devices and the possibility to bridge spatial and temporal communication boundaries. However, several researchers have raised privacy concerns due to the large amount of user data shared on OSNs. Yet, despite the large body of research addressing OSN privacy issues, little differentiation of data types on social network sites is made and a generally accepted classification and terminology for such data is missing. The lack of a terminology impedes comparability of related work and discussions among researchers, especially in the case of privacy implications of different data types. To overcome these shortcomings, this paper develops a well-founded terminology based on a thorough literature analysis and a conceptualization of typical OSN user activities. The terminology is organized hierarchically resulting in a taxonomy of data types. The paper furthermore discusses and develops a metric to assess the privacy relevance of different data types. Finally, the taxonomy is applied to the five major OSNs to evaluate its generalizability.

Conceptualising and Exploring User Activities in Social Media

“…installed applications, busy status, missed calls count, position from Graphical Position System (GPS) sensor, remaining battery power, and ringtone volume). Richthammer et al [22] identify 11 online social network (OSN) activities. Examples are "User posts Item/Comment", "User sends messages to Contact/Page", "User is linked to Item/Comment", and "Contact/Page views User's Profile".…”

“…Research on user activities in social media is contemporary and there are a number of existing conceptualisations [17][18][19]22]. These are valuable to understand the user's motivation of being active and show some features of social media.…”

Big Data Analytics for Large-scale Wireless Networks

“…(iii) Application data. In addition, data originates from the use of third party services, e.g., playing online-games, which can be offered by either the same social service provides or other service providers [33]. 2) User-related Data mainly refer to the data related to the personality and social interactions of users including the following sub-types: (i) User profile data are profilecentric data which can describe personality aspects of users, e.g., address, education, favorites, hobbies, etc.…”

Privacy in Social Networks: Existing Challenges and Proposals for Solutions

“…Despite the large body of research regarding privacy issues in SNS, there are rather fundamental aspects that have received little attention and that should be addressed first such as the differentiation of social network data types. Since the lack of a generally accepted terminology may lead to confusion in related discussions, we fill this gap by proposing a comprehensive taxonomy in [18,19]. This is particularly important considering the fact that the popularity of SNSs has lead to an increased quantity and availability of sensitive data.…”

“…We discover that privacy implications mainly depend on the interplay of a data element's content, the extent and the granularity of user control, and the concrete implementations of these factors on the respective platform. In the course of demonstrating the applicability of our taxonomy, we reveal the implementation-specific differences in privacy settings [18,19].…”