This master's thesis was written as part of the course of M.Tech program offered by Dept. of Computer Science and Technology, IIT Roorkee. The repo contains the presentations and reports submitted for the mid-year literature review and the final thesis. It also contains the summary of the related research papers that I consulted while researching on this topic. Students researching in this field can read the reports and the summaries for better understanding of the concepts.
Today there is vast amount of information/news available on the World Wide Web in theform of news articles, blogs and microblogs. Everyday the news media is filled with newsabout various entities commenting about different events. Thus each event generates aseries of conversations between different entities of interest. It would be very interestingfor a user to discover how a specific entity has conversed with other entities in the news media about various events happened within a certain time period.We propose a novel visualization technique, “Conversation Timeline” that chronologically displays the conversations of a given entity with other unknown entities which have been reported in news media. We have used news headlines to extract these conversations since news headlines contain the key idea of the comments made by an entity. We use relation extraction algorithm to retrieve conversations from the text. We propose a pre-processing step that syntactically alter the headlines so as the relation extraction module can generate better quality relations. We believe that a Conversation Timeline will give a better understanding about how an entity interacts with other entities of interest.