Current Apprises of Opinion Mining Methods
B. Manjula1, Ameen Abdullah Aqlan2, R. Lakshman Naik3
1B. Manjula, Department of Computer Science, Kakatiya University, Warangal, Telangana, India.
2Ameen Abdullah Aqlan, Department of Computer Science, Kakatiya University, Warangal, Telangana, India.
3R. Lakshman Naik, Dept. of IT, KU College of Engineering & Technology, Kakatiya University, Warangal, Telangana, India.
Manuscript received on November 27, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 3511-3516 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3906129219/2019©BEIESP | DOI: 10.35940/ijeat.B3906.129219
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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: Increasingly, the data is increasing day by day and storage capacity is expanding more and more, this allowing the field of SA to growing and developing faster in research and prospecting for different opinions and emotions to be combed and technically treated to be more accurate. In our present, data can be a wealth where major global companies and development, research and crime detection centers benefit from it. In this paper we focused on the current apprises of research in this field which contributed to various improvements in the field of sentiment analysis. We have tackles comprehensive overviews for different fields which related to the Sentiment Analysis (Transfer Learning (TL), Building Resource (BR), Emotion Detection (ED)) which have the popularity of researchers has gained in recent times and attracted them. We have the aim of this survey which is to give a clear and accurate picture about the techniques of analyzing emotions and related fields.
Keywords: Sentiment Analysis, NL Process, Emotion Detection, Data Mining, Building Resources.