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

作     者：Shu-Hung Yang Yi-Nan Lin Cheng-Ying Yang Ming-Kuen Chen Victor R.L.Shen Yu-Wei Lin Shu-Hung Yang;Yi-Nan Lin;Cheng-Ying Yang;Ming-Kuen Chen;Victor R.L.Shen;Yu-Wei Lin

作者机构：the Department of Business ManagementNational Taipei University of TechnologyTaipei 10608 the Department of Computer ScienceUniversity of TaipeiTaipei 100 the Department of Information ManagementChaoyang University of TechnologyTaichung 413 the Department of Computer Science and Information EngineeringNational Taipei UniversityNew Taipei 23741 

出 版 物：《Journal of Electronic Science and Technology》 (电子科技学刊（英文版）)

年 卷 期：2022年第20卷第2期

页      面：209-223页

核心收录：

学科分类：08[工学] 081203[工学-计算机应用技术] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by project under Grants No.MOST 107-2221-E-845-001-MY3 and No.MOST 110-2221-E-845-002 

主　　题：own correctness companies 

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.