Open AccessSentiment of App with Word Vectors
Author(s) -
M. Preethi,
C.V.P.R. Prasad
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1416.0986s319
Subject(s) - computer science , sentiment analysis , word (group theory) , artificial intelligence , polarity (international relations) , natural language processing , domain (mathematical analysis) , support vector machine , quality (philosophy) , bag of words model , mathematics , mathematical analysis , philosophy , genetics , geometry , epistemology , biology , cell
Vector representations for language have been shown to be useful in a number of Natural Language Processing tasks. In this paper, we aim to investigate the effectiveness of word vector representations for the problem of Sentiment Analysis. In particular, we target three sub-tasks namely sentiment words extraction, polarity of sentiment words detection, and text sentiment prediction. We investigate the effectiveness of vector representations over different text data and evaluate the quality of domain-dependent vectors. Vector representations has been used to compute various vector-based features and conduct systematically experiments to demonstrate their effectiveness. Using simple vector based features can achieve better results for text sentiment analysis of APP.