Multi Participant Chat Analysis


K. Anita Davamani,S.Amudha,



web-based social networking,measure of data,(NIA) rely on data,


Human practices have dependably been of incredible enthusiasm to analysts and researchers. Surmising positive and negative suppositions from discussion has been something which humanity has dependably had enthusiasm from an earlier time. With the appearance of web-based social networking channels, the measure of data we are getting about people and their practices is enormous. Internet based life has brought the discussions of individuals as content which can be handled, and inductions can be made. At present there exists a ton of work in the field of slant examination and there have been a couple of web administrations which use feeling investigation for impact positioning and brand gathering figuring. In my project, my research work is focused on analyzing massive group chats and dividing them separately for every user by clustering them based on gap between them. It can be very useful for societies, Business farms, National Security and in many other fields. Because in today’s world where everybody is interested rely on the data harvesting and What people are talking about. From a big cooperation to National Investigation Agencies (NIA) rely on data about the conversation between people’s what they are more commonly talking about and is there anything odd in those conversations. But a big question arise as there are thousands of groups and they have hundreds of members and thousand’s of messages out of them there few ones who participate actively while there are many members who rarely send messages in those groups and in those thousand’s of messages there is some particular words which are used more commonly and while there are also words which get used rarely. So how to classify all this information? Can we rely on manual classification? Or do we need program to automatically do this work for us and presenting in form of graphs?


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