DOI: https://doi.org/10.14710/vol15iss2pp227-236

Review of Systematic Literature about Sentiment Analysis Techniques

*Cornelius Damar Sasongko  -  Doctoral Program of Information System, School of Post Graduate Studies, Diponegoro University, Jl. Imam Bardjo S.H., No. 5, Pleburan, Semarang, Indonesia 50241, Indonesia
Rizal Isnanto  -  Doctoral Program of Information System, School of Post Graduate Studies, Diponegoro University, Jl. Imam Bardjo S.H., No. 5, Pleburan, Semarang, Indonesia 50241, Indonesia
Aris Puji Widodo  -  Department of Informatics, Faculty of Science and Mathematics, Diponegoro University, Jl. Prof. Soedarto, S.H., Tembalang, Semarang, Indonesia 50275, Indonesia
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Abstract

Sentiment analysis, also known as opinion mining, is an important task in natural language processing and data mining. It involves extracting and analyzing subjective information from textual data to determine the sentiment or opinion expressed by the author. With the advancement of technology and the widespread use of social media and online review platforms, it is increasingly important to understand users' opinions and sentiments regarding a particular product, service or issue. The purpose of this research is to present a comprehensive literature review on sentiment analysis techniques. This research utilizes the systematic literature review method. This method involves systematic steps in searching, evaluating, and analyzing relevant literature in the field of sentiment analysis. The literature search was conducted through scientific databases and other reliable sources. Relevant articles were then selected based on pre-determined inclusion and exclusion criteria. The data from the selected articles were then comprehensively analyzed to identify the sentiment analysis techniques used and the key findings in the research. The results show that there are various techniques and approaches that have been developed and tested in sentiment analysis, some of the commonly used techniques include rule-based methods, classification-based methods, and machine learning-based methods.

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Keywords: Sentiment Analysis; Opinion Mining; Natural Language Processing; Systematic Literature Review; Machine Learning Techniques

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Section: Research Articles
Language : EN
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