Analyzing Reactions on Political Issues in Social Media Using Hierarchical and K-Means Clustering Methods

Social media usage is undeniably getting larger, Currently, Twitter is one of the most popular social media platforms that enables its user to post their thoughts on anything, commonly in the form of limited word length. The massive number of Twitter users has made Twitter a valuable source of data in analyzing people behavior and tendency in reacting to a certain political issue. Unfortunately, the textual postings are difficult to analyze as the dimension of the data is too high to be clustered. One needs to find the most appropriate method to cluster Twitter posting with an acceptable clustering result. This study presents the clustering of Twitter users based on the most common words used by the users in reacting to a trending political issue. A comparative study between hierarchical clustering and k-means clustering methods are presented and discussed in this study, as well as the word trend or main topic of the issue by histogram and wordcloud.