Sentiment Analysis of Twitter Corpus Related to Artificial Intelligence Assistants

被引：0

作者：

Park, Chae Won ^{[1
]}

Seo, Dae Ryong ^{[1
]}

机构：

[1] Paul Math Sch, Chungcheongbuk Do, South Korea

来源：

2018 5TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND APPLICATIONS (ICIEA) | 2018年

关键词：

sentiment analysis; user research; artificial intelligence assistant; twitter corpus; lexicon;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Providing an enhancing experience is one of the most significant current issues in the user's research. A process that improves user's experience should be required to evaluate the usability and emotion. Above all, sentiment analysis based on user's opinions can be used to understand user's tendency. This paper aims to make a criterion what artificial intelligence assistant is statistically better. User's opinions about three artificial intelligence assistants from Twitter were collected and classified into positive, negative, neutral opinions by a lexicon named Valence Aware Dictionary and sEntiment Reasoner (VADER). Also, we analyzed tweets through independent samples T-test, Kruskal-Wallis test, and Mann-Whitney test to show the statistical significance among groups. The results suggested the highest rank of three artificial intelligence assistants by using statistical analysis.

引用

页码：495 / 498

页数：4

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