State-of-the-art in privacy preserving data mining
ACM SIGMOD Record
Preserving Privacy in Social Networks Against Neighborhood Attacks
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Data and Structural k-Anonymity in Social Networks
Privacy, Security, and Trust in KDD
Preserving the privacy of sensitive relationships in graph data
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
Semantic enrichment of twitter posts for user profile construction on the social web
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Online social honeynets: trapping web crawlers in OSN
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
A comparison of two different types of online social network from a data privacy perspective
MDAI'11 Proceedings of the 8th international conference on Modeling decisions for artificial intelligence
Preventing automatic user profiling in Web 2.0 applications
Knowledge-Based Systems
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Social networks have become an essential ingredient of interpersonal communication in the modern world. They enable users to express and share common interests, comment upon everyday events with all the people with whom they are connected. Indeed, the growth of social media has been rapid and has resulted in the adoption of social networks to meet specific communities of interest. However, this shared information space can prove to be dangerous in respect of user privacy issues. In addition to explicit ''posts'' there is much implicit semantic information that is not explicitly given in the posts that the user shares. For these and other reasons, the protection of information pertaining to each user needs to be supported. In this paper, we present a novel approach wherein the extraction of implicit and explicit information is derived from a small sample of a popular social network (Twitter) that seeks also to preserve user's privacy whilst maintaining information utility.