Title :
Taxonomy for Social Network Data Types from the Viewpoint of Privacy and User Control
Author :
Christian Richthammer;Michael Netter;Moritz Riesner;Gunther Pernul
Author_Institution :
Dept. of Inf. Syst., Univ. of Regensburg, Regensburg, Germany
Abstract :
The growing relevance and usage intensity of Online Social Networks (OSNs) along with the accumulation of a large amount of user data has led to privacy concerns among researchers and end users. Despite a 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, hence leading to confusion in related discussions. This paper proposes a taxonomy for data types on OSNs based on a thorough literature analysis and a conceptualization of typical OSN user activities. It aims at clarifying discussions among researchers, benefiting comparisons of data types within and across OSNs and at educating the end user about characteristics and implications of OSN data types. The taxonomy is evaluated by applying it to four major OSNs.
Keywords :
"Taxonomy","Data privacy","Privacy","Social network services","Terminology","Data models","Semantics"
Conference_Titel :
Availability, Reliability and Security (ARES), 2013 Eighth International Conference on
DOI :
10.1109/ARES.2013.18