TY  - JOUR
T1  - A Review on Sentiment Analysis: Approaches, Practices and Applications
AU - Ogochukwu, Okeke AU - Chinedum, Amaechi 
JO  - Asian Journal of Information Technology
VL  - 20
IS  - 4
SP  - 92
EP  - 98
PY  - 2021
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2021.92.98
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2021.92.98
KW  - Sentiment analysis
KW  -Naïve Bayes
KW  -SVM
KW  -opinion mining
KW  -unsupervised and supervised algorithms
AB  - Sentiment Analysis (SA) has recently become
the focus of many researchers because analysis of online
text is useful and demanded in many different
applications. Analysis of social sentiments is a trending
topic in this era because users share their emotions in
more suitable format with the help of micro blogging
services like twitter. Twitter provides information about
individual’s real-time feelings through the data resources
provided by persons. The essential task is to extract user’s
tweets and implement an analysis and survey. However,
this extracted information can very helpful to make
prediction about the user’s opinion towards specific
policies. The motive of this study is to perform a survey
on sentiment analysis algorithms that shows the utilizing
of different ML and Lexicon investigation methodologies
and their accuracy. The study also focuses on the three
kinds of machine learning algorithms for Sentiment
analysis-supervised, unsupervised algorithms.
ER  -