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Review of Computer Engineering Research

June 2019, Volume 6, 2, pp 84-91

A Survey on Sentiment Analysis Algorithms and Datasets

Reena G. Bhati

Reena G. Bhati 1

  1. Computer Science Department, Tilak Maharashtra Vidyapeeth, Pune, India. 1

on Google Scholar
on PubMed

Pages: 84-91

DOI: 10.18488/journal.76.2019.62.84.91

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Article History:

Received: 06 August, 2019
Revised: 10 September, 2019
Accepted: 14 October, 2019
Published: 02 December, 2019


In this paper we present a deep literature review on existing system for sentimental analysis. Basically sentimental analysis (SA) is the measurement of preference of people’s thoughts via natural language processing. The main aim of sentiment analysis is to know the orientation of the sentiment described in script. In recent decades the researcher focuses on the study various algorithms for relevant research results of the sentiment analysis. This research paper provides a comprehensive overview of this field's latest update. In this review, some recent proposed improvements of algorithms and various SA applications are explored and briefly described. The aim of this paper is to provide knowledge about the different method related to sentimental analysis also how they are classified, what the applications of this analysis.
Contribution/ Originality
This study contributes to the existing literature by studying the existing systems and showing the disadvantages and comparative analysis based on various parameters.


Data mining, Natural language processing (NLP), Sentimental analysis (SA), Convolutional neural network (CNN) unsupervised, learning, Text mining, Feature representation.


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This study received no specific financial support.

Competing Interests:

The author declares that there are no conflicts of interests regarding the publication of this paper.


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