| Title |
SVM and naive bayes classification ensemble method for sentiment analysis / |
| Authors |
Korovkinas, Konstantinas ; Danėnas, Paulius ; Garšva, Gintautas |
| DOI |
10.22364/bjmc.2017.5.4.06 |
| Full Text |
|
| Is Part of |
Baltic journal of modern computing.. Riga : University of Latvia. 2017, vol. 5, iss. 4, p. 398-409.. ISSN 2255-8942. eISSN 2255-8950 |
| Keywords [eng] |
sentiment analysis ; SVM ; Naiıve Bayes classification |
| Abstract [eng] |
This paper follows an important problem of sentiment recognition which may influence ones decisions or reviews about item and etc. In this paper we introduce a new method to improve classification performance in sentiment analysis, by combining SVM and Na¨ıve Bayes classification results to recognize positive or negative sentiment, and test in on datasets from movie reviews, sentiment140 and Amazon reviews. This method is evaluated on a training dataset which consists positive and negative words, and hold-out testing dataset, as well with training data from the same area. It was observed that better results were obtained using our proposed method in all the experiments, compared to simple SVM and Naıve Bayes classification. |
| Published |
Riga : University of Latvia |
| Type |
Journal article |
| Language |
English |
| Publication date |
2017 |
