Efficient Social Network Summarisation

Nowadays social media is playing important role in human life. Spreading of information is referred as information diffusion. While propagating information observing individual transmission i.e. who infects whom is very important. Few existing studies aim to study on static pattern but it is very difficult to trace the origin of information on evolving period of time. Dynamic network has some challenges like including 1) An event with particular topic evolves so rapidly with time. Usually it is very difficult to see every news/updates related to particular Event. 2) At the same time lots of events are happening so it is impossible to pay attention each & every event.3) Every topic in every event carries different news & different sentiment again it is difficult to analyse. To study information diffusion over underlying network, we have proposed SMS Framework which summarise the network evolving over time. The SMS system has considered interestingness of social media content as the factor to evaluate summarization in an online fashion. Interestingness factor is based on two common observations; First users are favouring social media rather than television for news & current updates. For example, consider any breaking news which goes on viral before telecasting on news channel. Second, it is observed that maximum communication & conversation takes place through social networks. Social communities are formed for social communication. Along with summarization SMS have also consider the polarity of each post such as positivism, negativism or neutral topic. Summarisation of social media is beneficial in academic research as well as many industries are interested in studying the user’s behaviour in social media.