Analysis and Visualization for Comment Messages of Internet Posts

There are many internet users who collect the public opinions and express their opinions for internet news or blog articles through the replying comment on online community. But, it is hard to search and explore useful messages on web blogs since most of web blog systems show articles and their comments to the form of sequential list. Also, spam and malicious comments have become social problems as the internet users increase. In this paper, we propose a clustering and visualizing system for responding comments on large-scale weblogs, namely `Daum AGORA,` using similarity analysis. Our system shows the comment clustering result as a simple screen view. Our system also detects spam comments using Needleman-Wunsch algorithm that is a well-known algorithm in bioinformatics.