As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
In this paper, a neural network is proposed to analyse Twitter sentiment classification for the Twitter domain. The study examines and evaluates the performance of neural networks with word embedding features in Twitter sentiment classification. Four benchmark datasets were used to represent different domains. The results indicated that the proposed method significantly improves the accuracy of the neural network classifier compared to existing works in aspect-based sentiment classification, especially for the highly imbalanced dataset.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.