Role of Machine Learning in Sentiment Analysis- A Review

Authors

  • Manitosh Chourasiya
  • Prof. Devendra Singh Rathore

Keywords:

Sentiment Analysis, Artificial Intelligence, Machine Learning, Natural Language Processing.

Abstract

Amongst the most basic activities in natural language processing is to know and understand low-dimensional vector presentations of words from a huge dataset. The organizational forms embedding system trains word vectors primarily from grammatical rules and semantic relations from the sense, disregarding sentiment polarity in the sentences. While some methods prototype sentiment data from feedback, they ignore specific language in various contexts. If the responded vector is easily adapted to the evaluation of sentiment classification task when the sentimentality keeps changing, the sentiment classification performance will suffer immensely. The methodologies was using to categories sentiment classification are discussed in this paper.

Author Biographies

Manitosh Chourasiya

M Tech Scholar

Rabindranath Tagore University

Bhopal, M.P, India

Prof. Devendra Singh Rathore

Assistant Professor

Rabindranath Tagore University

Bhopal, M.P, India

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Published

2022-01-24

How to Cite

Chourasiya, M. ., & Rathore, P. . D. S. (2022). Role of Machine Learning in Sentiment Analysis- A Review. SMART MOVES JOURNAL IJOSTHE, 8(4), 1–4. Retrieved from http://www.ijosthe.com/index.php/ojssports/article/view/173

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Articles