Abstract
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.
Published Version
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