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  Published Paper Details:

  Paper Title

ANALYSIS OF SENTIMENTS ON VOICE USING AWS COMPREHEND

  Authors

  Prof. (Mrs.) Vidya G. Shitole,  Ajinkya Kamble,  Pratik Naik,  Pratik Parbhane

  Keywords

AWS, AWS Comprehend, AWS transcribe, AWS lambda, Natural Language Processing, sentiment analysis.

  Abstract


Sentiment analysis or opinion mining is a field of study that analyses people's thoughts, opinions, behaviors, and emotions from written language. It is one of the most active research fields in natural language processing, and it is also frequently investigated in data mining, web mining, and text mining. In fact, because of its importance to business and society as a whole, this research has spread beyond computer science into management sciences and social sciences. The rise of social media platforms such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks parallels the rise of sentiment analysis. Sentiment analysis systems are adopted in practically every corporate and social field because opinions are significant to practically everyone's work and influence our behavior. In our study, we will use AWS cloud services to analyse sentiments. The future and one of the most remarkable technical advancements in the technological world are cloud computing. AWS consists of so many distinct cloud computing products and services. Cloud services for the general public are the fastest expanding. The AWS services are also used more quickly and accurately.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2107129

  Paper ID - 209767

  Page Number(s) - b54-b60

  Pubished in - Volume 9 | Issue 7 | July 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Prof. (Mrs.) Vidya G. Shitole,  Ajinkya Kamble,  Pratik Naik,  Pratik Parbhane,   "ANALYSIS OF SENTIMENTS ON VOICE USING AWS COMPREHEND", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 7, pp.b54-b60, July 2021, Available at :http://www.ijcrt.org/papers/IJCRT2107129.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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