Title :
Effect of using regression in sentiment analysis
Author :
Önal, Itir ; Ertuğrul, Ali Mert
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Orta Dogu Teknik Univ., Çankaya, Turkey
Abstract :
In this study, the effect of using regression on sentiment classification of Twitter data was analyzed. In other words, whether the strength of sentiment better discriminates the classes or not. Since our dataset includes class confidence scores rather than discrete class labels, regression analysis was employed on each class separately. Then, each tweet was assigned the class whose estimated confidence score is maximum among others after regression. The feature set used includes unigrams, POS tags, emoticons, sentiments of words and POS tags of sentiments. The results of experiments indicate that using classification on discrete class labels perform much better than using regression on continuous confidence scores.
Keywords :
regression analysis; social aspects of automation; social networking (online); Twitter data; discrete class labels; regression analysis; sentiment analysis; sentiment classification; Conferences; Libraries; Regression analysis; Robustness; Signal processing; Twitter; Twitter; confidence scores; regression; sentiment analysis;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
DOI :
10.1109/SIU.2014.6830606