Sentiment Analysis Based on Appraisal Theory for Assessing Incumbent Electability

Canrakerta Canrakerta, Pamuji Lasiyanto Putro, Zikri Irfandi, Nur Fitriah Ayuning Budi, Achmad Nizar Hidayanto
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引用次数: 1

Abstract

Sentiment analysis is a useful study for determining opinions by classifying text. The document used in the research comes from Twitter about public opinion about community satisfaction related to performance of incumbent. The method used is Appraisal Theory. The data used are 1587 for Jokowi related data, 1774 for Ministry related data, and 1337 government related data. The result of data analysis from this research is that people have positive sentiments for incumbent. Innovation is a term that has the highest positive sentiment, whereas imaging is the term that has the lowest negative sentiment.
基于评价理论的情感分析对现任总统可选性的评估
情感分析是通过对文本进行分类来确定观点的一项有用的研究。研究中使用的文件来自Twitter关于在职者绩效与社区满意度相关的公众意见。所使用的方法是评价理论。使用的数据有:Jokowi相关数据1587个,Ministry相关数据1774个,government相关数据1337个。本研究的数据分析结果表明,人们对在职者有积极的看法。“创新”是正面情绪最高的一个术语,而“成像”是负面情绪最低的一个术语。
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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