印度尼西亚人对南海争端的看法:支持向量机和奈夫贝叶斯方法

Adinda Aulia Hafizha, Nurfarah Nidatya
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引用次数: 0

摘要

近年来,印尼与中国的关系日益融洽。然而,随着南海争端的加剧,紧张局势的潜在根源正在显现。印尼政府被认为是中国的盟友,但印尼人对中国的负面看法由来已久,这影响了普通民众和政治精英对印尼与中国关系的看法。本研究有两个目标。首先是研究印尼人对南海冲突的看法。其次是比较支持向量机(SVM)和多项式奈夫贝叶斯(Multinomial Naïve Bayes)作为情感分析方法的性能。以社交媒体 X 上的 7.051 篇印尼语帖子为数据集,结果显示相当一部分印尼人对南海争端持负面看法,担心南海争端可能升级并威胁到国家安全。尽管存在这些担忧,但我们仍有理由相信,印尼可以在通过东盟和联合国海洋法公约框架解决冲突方面发挥积极作用。同时,SVM 已被证明是处理情感分析数据的有效方法,准确率高达 87.95%。这项研究强调了社交媒体这一有价值的平台,并证明了 SVM 的有效性,从而为情感分析领域做出了贡献。此外,本研究还通过机器学习视角分析了南海争端,为国际关系领域提供了新的见解,可能会带来新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Indonesians Perception on the South China Sea Dispute: Support Vector Machine and Naïve Bayes Approach
In recent years, relations between Indonesia and China have become increasingly cordial. However, a potential source of tension is emerging in the form of a heightened dispute in the South China Sea. The government of Indonesia is considered an ally, however there has been a long-standing negative opinion among Indonesians regarding China, which has influenced the way both the general public and the political elite have perceived the relations between Indonesia and China. This research has two objectives. The first is to examine Indonesian perceptions regarding the South China Sea conflict. The second is to compare the performance of Support Vector Machine (SVM) and Multinomial Naïve Bayes as a method of sentiment analysis. Using 7.051 Indonesian-language posts from social media X as a dataset, the result shows that a significant portion of Indonesians view the dispute negatively, fearing potential escalation and threats to national security. Despite these concerns, there is reason to believe that Indonesia can play a proactive role in resolving the conflict through ASEAN and UNCLOS frameworks. Meanwhile, SVM has been demonstrated to be an effective method for handling sentiment analysis data, achieving an accuracy of 87.95%. This work contributes to the field of sentiment analysis by highlighting social media as a valuable platform and by demonstrating the effectiveness of SVM. Furthermore, the study offers new insights for the field of international relations by analyzing the South China Sea dispute through a machine learning lens, which may lead to the development of novel perspectives.
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