Sentiment of App with Word Vectors
Preethi Kulkarni1, C.V.P.R. Prasad2
1Ms. Preethi, Assistant Professor, Department of Computer Science & Engineering, Malla Reddy Engineering College for Women, Hyderabad (Telangana), India.
2Dr. C.V.P.R. Prasad, Professor, Department of CSE, Malla Reddy Engineering College for Women, Hyderabad (Telangana), India.
Manuscript received on 01 November 2019 | Revised Manuscript received on 13 November 2019 | Manuscript Published on 22 November 2019 | PP: 2156-2159 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F14160986S319/19©BEIESP | DOI: 10.35940/ijeat.F1416.0986S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Sentiment Word Vectors Analysis Natural Language Processing.
Scope of the Article: Natural Language Processing