基于Naïve贝叶斯和k近邻算法的2020年亚洲杯印尼国家队情绪分析

Muhammad Ilham Fadila, Hanafi, Anggit Dwi Hartanto
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引用次数: 0

摘要

亚洲足球联盟杯是由东盟足球联合会(简称AFF)组织的足球比赛。由于新冠肺炎疫情,2020年亚洲杯在2021年举行。印尼国家队进入最后一轮,获得亚军。随着锦标赛结束,印度尼西亚国家队不得不接受决赛的失败,公众通过推特回应。通过这些推特,就可以知道公众是如何评价印尼国家队在2020年亚洲杯上的表现的。开展这项研究以获得有关社会反应的信息是至关重要的。将进行的研究是情绪分析。情感分析将在Rapid Miner软件上进行,使用的算法为Naïve Bayes和K-Nearest Neighbor。用于执行情感分析的数据是使用snscraper从Twitter获取的tweet。本研究旨在分析公众对2020年亚洲杯印尼国家队的反应。这项研究将从公众反应中确定积极、中性和消极情绪的百分比。这样就可以得出公众对印尼国家队的反应,是积极的、中立的还是消极的。同时也要找出哪种算法的准确率更高。对于准确率为64.74%的朴素贝叶斯,得到的结果是正面情绪为71.54%,中性情绪为15.45%,负面情绪为13.01%。对于k -最近邻居,准确率为65.64%的是80.49%的积极情绪,15.45%的中立情绪,4.06%的消极情绪。在执行情感分析时,这两种算法与Rapid Miner中的其他算法相比具有最高的准确性,其中k -最近邻的准确性略高。关于2020年亚洲杯印尼国家队的推文大多是积极的。根据这些结果,可以得出结论,即使印尼国家队没有赢得2020年亚洲杯,公众仍然积极响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis of the Indonesian National Team in the 2020 AFF Cup Using Naïve Bayes and K-Nearest Neighbor Algorithms
The AFF Cup is a football competition organized by the ASEAN Football Federation, or AFF for short. The 2020 AFF Cup was held in 2021 due to the COVID-19 pandemic. The Indonesian National Team advanced to the final round and became runner-up in the championship. With the end of the championship and the Indonesian National Team having to accept defeat in the final, the public responded through tweets on Twitter. Through these tweets, it will be known how the public evaluates the performance of the Indonesian National Team in the 2020 AFF Cup. It is vital to carry out this research to obtain information regarding society's response. The research that will be conducted is sentiment analysis. Sentiment analysis will be carried out on Rapid Miner software, with the algorithms used being Naïve Bayes and K-Nearest Neighbor. The data used to perform sentiment analysis are tweets from Twitter taken using SNScrape. This research aims to analyze public responses to the Indonesian National Team in the 2020 AFF Cup. This research will determine the percentage of positive, neutral, and negative sentiments from public responses. So that later it can be concluded how the public responds to the Indonesian National Team, whether positive, neutral, or negative. It is also to find out which algorithm has the higher accuracy. The results obtained for Naive Bayes with an accuracy of 64.74% are 71.54% positive sentiment, 15.45% neutral sentiment, and 13.01% negative sentiment. For K-Nearest Neighbor, with an accuracy of 65.64% is 80.49% positive sentiment, 15.45% neutral sentiment, and 4.06% negative sentiment. Both algorithms have the highest accuracy compared to other algorithms in Rapid Miner when the sentiment analysis is performed, with K-Nearest Neighbor having slightly higher accuracy. Most tweets about the Indonesian National Team in the 2020 AFF Cup had positive sentiments. Based on these results, it can be concluded that even though the Indonesian National Team did not win the 2020 AFF Cup, the public still responded positively.  
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