The social graph is the basic construct of a social network maintaining registered network entities as nodes and relations amongst these entities as edges.
Published in Chapter:
Social Networking and Privacy: A Contradiction?
Steffen Ortmann (IHP, Germany), Peter Langendörfer (IHP, Germany), and Michael Maaser (IHP, Germany)
Copyright: © 2012
|Pages: 21
DOI: 10.4018/978-1-61350-168-9.ch047
Abstract
Social networks recently came under severe criticism for easy-going handling of user data. Millions of users voluntarily release private and business data without considering potential impacts on their real life that may come along with that. Used for personalized advertising or attendee profiling, user data are of utmost importance for economic success of the maintaining network. Hence, platform providers exploit all promising options to gather data while privacy and data security seem partially to be a pain for them. Dozens of security lacks and data thefts have emerged for almost every available platform. In addition, techniques and methods exist to secretly gather more user data, e.g., by proper fusion of miscellaneous information, analysis of visited websites, or social games. Even worse, misuse or rather sale of user data might be part of the marketing concept. This chapter analyzes the business networks LinkedIn and Xing, and the more leisure time related social communities Facebook and StudiVZ. In particular, differences in collecting and handling of user data are of interest. Based on that, we present and analyze reported criticism based on published and on own investigated data. Then we evaluate whether that criticism is justified, hypercritical, or understatement. On behalf of analyzing potential threats and pitfalls, we finally work out existing and potential privacy risks as well as resulting consequences for the real life of community members.