Validating Sentiment Analysis on Opinion Mining Using Self-reported Attitude Scores

被引：5

作者：

Featherstone, Jieyu Ding ^{[1
]}

Barnett, George A. ^{[1
]}

机构：

[1] Univ Calif Davis, Dept Commun, Davis, CA 95616 USA

来源：

2020 SEVENTH INTERNATIONAL CONFERENCE ON SOCIAL NETWORK ANALYSIS, MANAGEMENT AND SECURITY (SNAMS) | 2020年

关键词：

sentiment analysis; attitude; opinion mining; surveys; validation;

D O I：

10.1109/SNAMS52053.2020.9336540

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper aims to validate the use of sentiment analysis of text on opinion mining, using IBM Watson's Natural Language Understanding. An online survey examining attitude towards genomic editing using a validated scale and a text entry to comment on their thoughts of this technology was given to four populations-scientists, policymakers, farmers and the general public. The results indicate that sentiment scores of texts are significantly related to attitude scores in three of the four populations. This study shows that sentiment analysis is a reliable tool to understand opinions.

引用

页码：166 / 169

页数：4

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