文章基本信息

标题：Subjectivity Analysis in Opinion Mining - A Systematic Literature Review
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作者：Emaliana Kasmuri ; Halizah Basiron
期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2017
卷号：9
期号：3
页码：132
出版社：International Center for Scientific Research and Studies
摘要：Subjectivity analysis determines existence of subjectivity in text using subjective clues. It is the first task in opinion mining process. The difference between subjectivity analysis and polarity determination is the latter process subjective text to determine the orientation as positive or negative. There were many techniques used to solve the problem of segregating subjective and objective text. This paper used systematic literature review (SLR) to compile the undertaking study in subjective analysis. SLR is a literature review that collects multiple and critically analyse multiple studies to answer the research questions. Eight research questions were drawn for this purpose. Information such as technique, corpus, subjective clues representation and performance were extracted from 97 articles known as primary studies. This information was analysed to identify the strengths and weaknesses of the technique, affecting elements to the performance and missing elements from the subjectivity analysis. The SLR has found that majority of the study are using machine learning approach to identify and learn subjective text due to the nature of subjectivity analysis problem that is viewed as classification problem. The performance of this approach outperformed other approaches though currently it is at satisfactory level. Therefore, more studies are needed to improve the performance of subjectivity analysis.
关键词：opinion mining; sentiment analysis; subjectivity analysis; systematic literature review.