Sentiment Analysis Research in Indonesian Language Reviewing From the Characteristics of Comments
Abstract
This study focuses on identifying the method of sentiment analysis using the data sources from different social media. The comments are classified based on the themes: politics, business product reviews, events, etc. The study also focuses on the form of the language and the data types: text only and texts with emoticons. The literature review is conducted on several previous studies with characteristics: Indonesian language, sarcasm, the method used, and the development of certain features in the sentiment analysis method. There are three conclusions. First, there are polite comments and impolite/ sarcastic comments. Comments posted on government channels are more polite than those on social media channels. All the comments have the same polarity. The comments use words only or a combination of words and emoticons. The analysis becomes complex because the comments use slang words. Second, the support vector machine (SVM) method is widely used. The use of libraries in doing sentiment analysis in Indonesian is helpful, but only a few are suitable for general purposes. Finally, the feature development has many variants which can be customized based on the needs, and SentiWordNet is the most popular supporting application.
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DOI: http://dx.doi.org/10.52155/ijpsat.v32.2.4341
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