Real-Time Incremental Clustering on Social Network Comment Streams using Enhanced IncreSTS Algorithm

Popularity of social networking sites increases day by day. Due to its high popularity, the number of comments can grow at a high rate when a social message published. The users of social networking sites may wish to get a brief knowledge of comment streams without reading the all comments. The system aim to group comments with similar opinion together and create a summary for this message after filtering abusive words from each generated comments. Since the users will request the summary at any moment, we use IncreSTS algorithm for realtime incremental clustering of social network comment streams. Besides, we extract key-terms from each clusters that help users to easily get an overview summary.