Open AccessRefined distributed emotion vector representation for social media sentiment analysis
Author(s) -
Yung Chun Chang,
Wen Chao Yeh,
Yan Chun Hsing,
Chen Ann Wang
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0223317
Subject(s) - sentiment analysis , computer science , vocabulary , social media , representation (politics) , process (computing) , data science , key (lock) , information retrieval , artificial intelligence , latent semantic analysis , support vector machine , natural language processing , world wide web , philosophy , linguistics , computer security , politics , political science , law , operating system
As user-generated content increasingly proliferates through social networking sites, our lives are bombarded with ever more information, which has in turn has inspired the rapid evolution of new technologies and tools to process these vast amounts of data. Semantic and sentiment analysis of these social multimedia have become key research topics in many areas in society, e.g., in shopping malls to help policymakers predict market trends and discover potential customers. In this light, this study proposes a novel method to analyze the emotional aspects of Chinese vocabulary and then to assess the mass comments of the movie reviews. The experiment results show that our method 1. can improve the machine learning model by providing more refined emotional information to enhance the effectiveness of movie recommendation systems, and 2. performs significantly better than the other commonly used methods of emotional analysis.