Modeling and Verification of a Sentiment Analysis System Using Aspect-Oriented Petri Nets

被引：0

作者：

ShuHung Yang ^{[1
]}

YiNan Lin ^{[2
]}

ChengYing Yang ^{[3
]}

MingKuen Chen ^{[1
]}

Victor RLShen ^{[4
]}

YuWei Lin ^{[5
]}

机构：

[1] the Department of Business Management, Taipei University of Technology

[2] the Department of Electronic Engineering,Ming Chi University of Technology

[3] the Department of Computer Science,University of Taipei

[4] the Department of Information Management,Chaoyang University of Technology

[5] the Department of Computer Science and Information Engineering, Taipei

来源：

Journal of Electronic Science and Technology | 2022年 / 20卷 / 02期

关键词：

D O I：

暂无

中图分类号：

TP301.1 [自动机理论]; TP391.1 [文字信息处理];

学科分类号：

摘要：

An increasing number of social media and networking platforms have been widely used. People usually post the online comments to share their own opinions on the networking platforms with social media. Business companies are increasingly seeking effective ways to mine what people think and feel regarding their products and services. How to correctly understand the online customers’ reviews becomes an important issue. This study aims to propose a method with the aspect-oriented Petri nets(AOPN) to improve the examination correctness without changing any process and program. We collect those comments from the online reviews with Scrapy tools, perform sentiment analysis using SnowNLP, and examine the analysis results to improve the correctness. In this paper, we apply our method for a case of the online movie comments. The experimental results have shown that AOPN is helpful for the sentiment analysis and verifying its correctness.

引用

页码：209 / 223

页数：15

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