Title :
An empirical study on sentiment analysis for Vietnamese
Author :
Nguyen Thi Duyen ; Ngo Xuan Bach ; Tu Minh Phuong
Author_Institution :
Dept. of Comput. Sci., Posts & Telecommun. Inst. of Technol., Hanoi, Vietnam
Abstract :
This paper presents an empirical study on machine learning based sentiment analysis for Vietnamese, in which we focus on the task of sentiment classification. We investigate the task regarding both learning model and linguistics feature aspects. We also introduce an annotated corpus for sentiment classification extracted from hotel reviews in Vietnamese and conduct a series of experiments and analyses on that corpus. The paper provides useful information for further research as well as for building a real sentiment analysis system for Vietnamese.
Keywords :
learning (artificial intelligence); natural language processing; pattern classification; Vietnamese; annotated corpus; hotel reviews; learning model; linguistics feature aspects; machine learning; sentiment analysis; sentiment classification; Accuracy; Entropy; Feature extraction; Learning systems; Sentiment analysis; Support vector machines; Training; Maximum Entropy Models; Naive Bayes; Sentiment Analysis; Support Vector Machines;
Conference_Titel :
Advanced Technologies for Communications (ATC), 2014 International Conference on
Print_ISBN :
978-1-4799-6955-5
DOI :
10.1109/ATC.2014.7043403