Verb Based Sentiment Research
A. Sharada1, P. Preethi Krishna2
1Dr. A. Sharada, Department of CSE, G. Narayanamma Institute of Technology & Science, Hyderabad (Telangana), India.
2P. Preethi Krishna, Department of CSE, G. Narayanamma Institute of Technology & Science, Hyderabad (Telangana), India.
Manuscript received on 15 October 2019 | Revised Manuscript received on 24 October 2019 | Manuscript Published on 02 November 2019 | PP: 2468-2471 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B12890982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1289.0982S1119
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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: Sentiment Analysis is one of the leading research work. This paper proposes a model for the description of verbs that provide a structure for developing sentiment analysis. The verbs are very significant language elements and they receive the attention of linguistic researchers. The text is processed for parts-of-speech tagging (POS tagging). With the help of POS tagger, the verbs from each sentence are extracted to show the difference in sentiment analysis values. The work includes performing parts-of-speech tagging to obtain verb words and implement Text Blob and VADER to find the semantic orientation to mine the opinion from the movie review. We achieved interesting results, which were assessed effectively for accuracy by considering with and without verb form words. The findings show that concerning verb words accuracy increases along with emotion words. This introduces a new strategy to classify online reviews using components of algorithms for parts-of-speech.
Keywords: Parts-of-Speech (POS) Tagging, Verb Words, Text Blob and VADER.
Scope of the Article: Agent-Based Learning and Knowledge Discovery