Analysis of Feature Selection Methods for Sentiment Analysis Concerning Covid-19 Vaccination Issues

Muhammad, Fajar and Tri Basuki, Kurniawan and Edi Surya, Negara Harahap (2023) Analysis of Feature Selection Methods for Sentiment Analysis Concerning Covid-19 Vaccination Issues. Journal of Data Science, 2023 (03). pp. 1-13. ISSN 2805-5160

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Sentiment analysis or opinion mining is a computational study of a person's opinions, sentiments, evaluations, attitudes, moods, and emotions. Sentiment analysis is one of the most active research areas in natural language processing, data mining, information retrieval, and web mining. One of the problems identified in the sentiment analysis process is the massive amount of data or text properties. In sentiment analysis, each word or term is collected into properties or dimensions, forming a data table. Due to the vast number of terms, this causes the process to take too long and requires a computer with tremendous power or ability. In addition, this can lead to a decrease in the quality of the model because data that is too large will also provide a significant bias value. Not all terms have contributions or relationships to decisions or labels in the form of positive, negative, and neutral values. For this reason, the feature selection method will be used in this study to select features or terms that contribute more to decisions or labels. It is also hoped that this can increase the quality of the prediction model that will be formed. In this study, the author will continue the research from another researcher by adding a feature selection process, such as two algorithms from the filtered method, chi-square, and information gain, and one algorithm from the wrapped method, which is Genetic Algorithms (GA). The experiment result shows that the GA obtained result has the highest accurate value compared to the other methods.

Item Type: Article
Uncontrolled Keywords: Sentiment Analysis, Feature Selection, Filtered Method, Wrapped Method
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Depositing User: Unnamed user with email
Date Deposited: 23 Mar 2023 07:19
Last Modified: 13 Jul 2023 08:29

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