Panoptical View of the Sentiment Analysis Techniques
Geetika Vashisht1, Manisha Jailia2
1Geetika Vashisht*, Assistant Professor, Department of Computer Science, Delhi University India.
2Manisha Jaillia, Assistant Professor, Department of Computer Science, Delhi University India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2009-2016 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9537109119/2019©BEIESP | DOI: 10.35940/ijeat.A9537.109119
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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 (SA) is a rapidly evolving field that aims at computationally categorizing the opinions of people about a particular product, movie, brand or anything that can be opined. It has changed the way the information is perceived and utilized by big business groups, brands and marketing agencies by demonstrating that the computational recognition of a sentimental expression is feasible. The fruition of Internet based applications has generated huge amount of personalized views on the Web. These reviews exist in different forms like social Medias, blogs, Wiki or forum websites. The boom of search engines like Yahoo and Google has flooded users with copious amount of relevant reviews about specific destinations, which is still beyond human comprehension. Sentiment Analysis poses as a powerful tool for users to extract the needful information, as well as to aggregate the collective sentiments of the reviews. This research will explore and compare the various techniques used for Sentiment Analysis in the last decade.
Keywords: Sentiment Analysis(SA); Sentiments; Lexicons; Machine Learning(ML).