Media Sentiment Analysis of East Java Province: Lexicon-Based vs Machine Learning

Abstract

Indonesian Ministry of Communication and Informatics reported internet users in Indonesia reached 150 million with a penetration of 56% in January 2019. This indicates the era of information disclosure; therefore, information on government performance is more easily obtained by all levels of society. Society is becoming more sensitive to government performance, and more feedback is being given to the government. This large amount of feedback has stimulated research on public sentiment analysis. This study compares the public sentiment analysis by two different approaches to the government performance of East Java Province. The study was comparing the lexicon-based method approach and the Support Vector Machine (SVM) from the machine learning approach. This study uses Twitter and Instagram datasets, and also the online news media web that reports on East Java. This study found that by using a combined data source of social media and online media, the lexicon-based approach produced an accuracy value of 57.7%; while the SVM machine learning method approach produces an accuracy of 44.7%.