International Journal of Informatics and Communication Technology (IJ-ICT)
Vol 13, No 3: December 2024

Optimized support vector machine for sentiment analysis of game reviews

Supriyatna, Bryan Leonardo (Unknown)
Putri, Farica Perdana (Unknown)



Article Info

Publish Date
01 Dec 2024

Abstract

The rapid development of games has made game categories diverse, so there are many opinions about games that have been released. Sentiment analysis on game reviews is needed to attract potential players. Sentiment analysis is carried out using the support vector machine (SVM) and particle swarm optimization (PSO) algorithms. SVM training was conducted with a linear kernel, the ā€˜C’ value parameter was 10 resulting in an accuracy value of 97.28%. The SVM algorithm optimized using the PSO method produces an accuracy of 97.61% using the parameters c1 is 0.2, c2 is 0.5 and w is 0.6. Based on these results, sentiment analysis using PSO-based SVM optimization has been successfully carried out with an increase in accuracy of 0.33%. This game review has a sentiment value from neutral to positive so this game can be recommended to other players.

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Journal Info

Abbrev

IJICT

Publisher

Subject

Computer Science & IT

Description

International Journal of Informatics and Communication Technology (IJ-ICT) is a common platform for publishing quality research paper as well as other intellectual outputs. This Journal is published by Institute of Advanced Engineering and Science (IAES) whose aims is to promote the dissemination of ...