期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2017
卷号：17
期号：7
页码：100-105
出版社：International Journal of Computer Science and Network Security
摘要：Social media sites are the major source of user generated information on politics, products, ideas and services. Recently social media has become a value able resource for mining sentiment and opinions of public if the data is extracted from it reliably. In this study, a new framework is presented that uses social media network (twitter) stream data as an input and provide output in the form of identified sentiments. The main contribution of this research is a framework that employs data mining and machine learning techniques and analyzes the sentiments by using social network data. Research work has been done on social network website twitter. TF-IDF technique along with Na?ve Bayes performed better (Accuracy 81.24%) in comparison with the other well-known classifiers.
关键词：Social networks; Sentiment analysis; TF-IDF; Data mining; Recommender system.
