Word-forest Visualization of Discussed Topics in Social Media Comments

Abstract

It becomes a norm for many organizations to use social network as a platform for internal and external communication means. Due to its extensive usage, most large organizations recognize the importance of capturing disseminated information across the social networks for the benefit of their internal perusal. However, managing and keeping track of all the information which are hidden in the piles of comments are hard to deal with. This paper presents a system that can extract, analyze and visualize information from the comments. As for the case study, Facebook is chosen due to its ability to allow people to comment freely and repetitively. The comments were extracted from selected post in Facebook using its API. The relationship between the words inside the comments will then be determined by using relationship table. Then, a visualization technique, word-forest, is used to visualize the relation between the prepared table. The prototype is tested by using selected posts in specific Facebook accounts. The result shows that users can quickly get overviews on the topics that have been discussed without having to go through all the comments on the Facebook. The system has great potential to be further explored as one of the means to get internal and external workers or public perception unobtrusively at real-time and real-life setting.