This paper presents work-in-progress towards a computational approach for capturing a type of deviant behaviors, that are characterised by persistent monitoring and information gathering through online social medias. Such behaviors are commonly associated with stalking on the cyberspace. We present a network-based framework for describing online user interactions. Based on this framework we provide a description of excessive and unreciprocated attention an agent pays to another agent. We conclude with a discussion on limitation of the current work and a guideline for future extensions.

With the development of the Internet, more and more people actively interact with others via online social networks. Potentially, people can hide themselves in the dark and continually gather information from other users from the Internet. To assist individual users to protect their privacy and security, in this paper a computational approach for abnormal attention detection is presented. The proposed approach can detect abnormal attention from the local view of a user, without invading other people's privacy.

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