arXiv:1905.06643

Machine Learning based English Sentiment Analysis

T. N. T. Tran, L. K. N. Nguyen, V. M. Ngo

제출 2019-05-16

원문 초록

Sentiment analysis or opinion mining aims to determine attitudes, judgments and opinions of customers for a product or a service. This is a great system to help manufacturers or servicers know the satisfaction level of customers about their products or services. From that, they can have appropriate adjustments. We use a popular machine learning method, being Support Vector Machine, combine with the library in Waikato Environment for Knowledge Analysis (WEKA) to build Java web program which analyzes the sentiment of English comments belongs one in four types of woman products. That are dresses, handbags, shoes and rings. We have developed and test our system with a training set having 300 comments and a test set having 400 comments. The experimental results of the system about precision, recall and F measures for positive comments are 89.3%, 95.0% and 92,.1%; for negative comments are 97.1%, 78.5% and 86.8%; and for neutral comments are 76.7%, 86.2% and 81.2%.

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공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

논문 ID: publication/3527808공통 태그 BIG-bench Machine Learning, Sentiment Analysis

Twitter Sentiment Analysis

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