Graph Depicting User Interests through Text Mining Analysis

In today’s world, Social media based e-communication has become the most widely used platform to communicate and people make use of instant chat features to talk, share and spread each other’s ideas. With the help of Instant Messenger (IM), users can easily login to the messenger and can start the chat. The chat history is generally maintained in the messenger backend. Generally, these IM’s are used to chat and share ideas but users can also share the suspicious ideas on the IM. In this paper, the existing work for the detection of suspicious chat logs is presented. This paper also presents a framework based on Apriori Algorithm and linear SVM algorithm for the detection of suspicious chat activities. The research is based on taking these very instant chat logs and performing text mining techniques to it so that we can identify the users interest in various chat sessions. Text mining approaches are applied on chat log data and hence find the particular patterns and trends of words being used to find users motive.