Analyzing Twitter Social Media User Responses To Fs Cases Using Sentiment Analysis And Text Mining

Abstract

There are several factors behind the research on analyzing the response of social media users, especially on Twitter, to the Ferdy Sambo case. Some of these factors include the increasing use of social media and the widespread adoption of platforms like Twitter in Indonesia to comment on or express opinions about various matters or cases, particularly the Ferdy Sambo case which is the focus of this research. The purpose of this study is to determine how Twitter users respond to the Ferdy Sambo case and to assess the sentiment analysis results from Twitter users based on three categories: positive, negative, and neutral sentiments. Through the utilization of sentiment analysis and text mining, this research aims to uncover commonly used words in comments and responses from Twitter users regarding this case. These frequently used words will then be visualized using word clouds to display both their prevalence and frequency. Based on the analysis conducted, the findings reveal that out of the 15,002 data points, the words or opinions expressed by Twitter users are predominantly negative. These outcomes are further substantiated by accuracy, precision, and recall rates calculated at 97%, 95%, and 90%, respectively. The implications of this study are anticipated to offer insights into the responses of social media users towards a particular case, wherein negative situations generally elicit pessimistic opinions and vice versa. Moreover, it is envisaged that this research could serve as a foundation for future studies on similar subjects or employing similar methodologies.