Abstract
The sheer size of e-mail and instant messages received on daily basis by clients using mobile applications has created a usage scenario where users have to be conscious of their safety and manage information effectively in order to derive benefits from online interaction. This is moreso in organizations where e-mails and instant messages are frequently used as a means of communication through anonymous peer-to-peer systems (P2P). Using Use-Case schemes, we present a framework for profiling user behaviour on anonymous peer to peer networks. The framework presented is suggestive of employing data mining techniques to analyze entire sets of active and offline e-mails and instant messages sent and received by individual users. The implementation of this framework is expected to yield a recommender system for prioritizing e-mails and instant messages based on usage patterns between contacts and groups to which users belong. Keyword: Behaviour, chat, Data mining, e-mail, instant messages and recommender systems.
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