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An In-depth Analysis of Categorized Mining Algorithms for Opinion Mining

Shubham Bhardwaj

National Institute of Technology, Hamirpur, Himachal Pradesh

53-57

Vol: 10, Issue: 1, 2020

Receiving Date: 2020-01-10 Acceptance Date:

2020-03-05

Publication Date:

2020-03-29

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http://doi.org/10.37648/ijrst.v10i01.011

Abstract

Today's information and ideas can't be shared without social media. A person's day-to-day life is significantly affected by their emotional impact. An ecosystem that generates millions of bytes of data daily makes sentiment analysis essential for interpreting these enormous amounts of data. Sentiment analysis, a type of text mining, finds and extracts personal information from various sources, allowing businesses to monitor social sentiment about their brand, product, or service. Simply put, sentiment analysis enables one to ascertain the author's perspective on a topic. Writing is categorized as either positive, neutral, or negative by the software for sentiment analysis. With the help of deep learning algorithms and natural language processing functions, written or spoken sentiments about a topic can be better understood.

Keywords: social media; Sentimental Analysis; twitter

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