基于支持向量机算法的Moba游戏评论情感分析

Alif Fajar Panjalu, Syariful Alam, Mochammad Imam Sulistyo
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引用次数: 0

摘要

MOBA作为当今众多热门子类型之一,基于大量下载量的《Mobile Legend》、《Arena of Valor》、《League of Legend》和《Lokapala》可以说是热门的MOBA游戏,但这四款应用在Google Play平台Store的评分都在4.0以下,出现这种情况是因为一些用户可能认为这款手机MOBA游戏有几个优点,但也有一些缺点影响了评分。本研究旨在利用Google Play Store评论对手机MOBA游戏进行情感分析。然后使用Python编程对其进行处理,利用线性核支持向量机(SVM)算法建立模型,对数据集进行分类。从19579个数据的分类模型测试结果来看,其中正面情绪数据10017个,负面情绪数据9562个,列车数据和测试数据的分布为70%:30%,得到准确率为82.64%,然后使用交叉验证方法重新评估5次,准确率为83.38%为obtainedÂ关键词:MOBA,情绪分析,机器学习,SVM,交叉验证
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MOBA GAME REVIEW SENTIMENT ANALYSIS USING SUPPORT VECTOR MACHINE ALGORITHM
MOBA as one of the many popular subgenres today, Mobile Legend, Arena of Valor, League of Legend and Lokapala based on the large number of downloads can be mentioned as popular MOBA games, but the rating of these four applications is below 4.0 on the Google Play platform Store, this happens because some users may think that this mobile MOBA game has several advantages, but also some disadvantages that affect ratings. This study aims to determine the results of sentiment analysis on mobile MOBA games using Google Play Store reviews. Then it is processed using Python programming to create a model with the linear kernel Support Vector Machine (SVM) algorithm to classify the dataset. From the results of the classification model test using 19,579 data, where there were 10,017 positive sentiment data and 9,562 negative sentiment data and the distribution of train data and test data was 70%: 30%, obtained an accuracy of 82.64% and then re-evaluated using the Cross Validation method using 5 times so that an accuracy of 83.38% is obtained Keywords: MOBA, Sentiment Analysis, Machine Learning, SVM, Cross Validation
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