The Influence of Negation Handling on Sentiment Analysis in Bahasa Indonesia

Annisa Maulida Ningtyas, Guntur Budi Herwanto
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引用次数: 3

Abstract

The negation handling has not been the main focus in Bahasa Indonesia sentiment analysis so that sentence's polarity that has the word negation cannot be determined automatically. This study aimed to analyze the effect of negation handling in Bahasa Indonesia using First Sentiment Word (FSW), Rest of Sentence (ROS) and Fixed Window Length (FWL) with $\mathbf{n}= 1-5$. FSW will change the sentiment polarity of the first word after negation word, RoS will change the sentiment polarity of the entire word after the negation word, and FWL will change the polarity of sentiment words that exist in the scope of its window size. Results from this study indicate that the negation handling determined the sentence polarity optimally, compared to the absence of negation handling. FSW and FWL have an average accuracy increase by 2.43%, precision by 2.38%, and recall by 2.93%. FWL with $\mathbf{n}=3$ results the best with a precision, recall and accuracy value of 71.58%, 69.62%, 73.79% respectively. The negation handling on the automatic labeling process proved to be beneficial in increasing the performance of the classification.
否定处理对印尼语情感分析的影响
在印尼语情感分析中,否定处理一直不是重点,因此不能自动确定带有否定词的句子极性。本研究以$\mathbf{n}= 1-5$为条件,采用第一情感词(FSW)、句子剩余(ROS)和固定窗口长度(FWL)分析印尼语否定处理的效果。FSW会改变否定词后第一个词的情感极性,RoS会改变否定词后整个词的情感极性,而FWL会改变其窗口大小范围内存在的情感词的极性。研究结果表明,否定处理对句子极性的影响优于不加否定处理。FSW和FWL的平均正确率提高2.43%,精密度提高2.38%,查全率提高2.93%。$\mathbf{n}=3$的FWL效果最好,精密度为71.58%,召回率为69.62%,正确率为73.79%。在自动标注过程中进行否定处理有利于提高分类性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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