Aggregating and Analyzing Articles and Comments on a News Website

摘要

In the top news stories, the commenting activity is rising and falling until it stops. In some ongoing news stories such as disasters like the disappearance of flight MH370, global warming or climate change, political turmoil or economic crisis, this commenting activity cycle can repeat and last many years. To our knowledge, a study and analysis of those data does not exist up to now. There is a need to separate facts, opinions and junk within those comments data. In this paper, we present our framework for supporting readers in analyzing and visualizing facts, opinions and topics in the comments and its extension with comments aggregation and summarization for comments within several news articles for the same event. We added a time-series analysis and comments features such as surprising comments and a preferential threads attachment model.