期刊名称：International Journal of Modern Education and Computer Science
印刷版ISSN：2075-0161
电子版ISSN：2075-017X
出版年度：2019
卷号：11
期号：7
页码：32-43
DOI：10.5815/ijmecs.2019.07.04
出版社：MECS Publisher
摘要：Opinion Mining or Sentiment Analysis is the process of mining emotions, attitudes, and opinions automatically from speech, text, and database sources through Natural Language Processing (NLP). Opinions can be given on anything. It may be a product, feature of a product or any sentiment view on a product. In this research, Mobile phone products reviews, fetched from Amazon.com, are mined to predict customer rating of the product based on its user reviews. This is performed by the sentiment classification of unlocked mobile reviews for the sake of opinion mining. Different opinion mining algorithms are used to identify the sentiments hidden in the reviews and comments for a specific unlocked mobile. Moreover, a performance analysis of Sentiment Classification algorithms is performed on the data set of mobile phone reviews. Results yields from this research provide the comparative analysis of eight different classifiers on the evaluation parameters of accuracy, recall, precision and F-measure. The Random Forest Classifiers offers more accurate predictions than others but LSTM and CNN also give better accuracy.
