News event time-lines

Abstract

As the amount of news portals increases, huge amounts of news stories are being published every hour which leads to an information overload problem, and readers cannot digest it all. When reading a news report about an event, readers would find it useful to be able to conceptualise how that event unfolded without needing to read through all the previous news reports. This research focuses on implementing a live system News Event Time-lines(NETs) that creates a visualization interface that uses automatically generated time-lines from news sources to represent news events. The process involved many different stages, starting from the extraction of news stories, feature extraction, clustering into news events, and the timeline visualizations. The purpose of this system is to show the evolution of news events and how they relate with each other. A user study was conducted where participants made use of NETs showed promising results about the usefulness of the system, if it were to be extended further.