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Sentiment Analysis Approach based N-gram and KNN Classifier

by Akashdeep Dhiman, Dinesh Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 4
Year of Publication: 2018
Authors: Akashdeep Dhiman, Dinesh Kumar
10.5120/ijca2018917513

Akashdeep Dhiman, Dinesh Kumar . Sentiment Analysis Approach based N-gram and KNN Classifier. International Journal of Computer Applications. 182, 4 ( Jul 2018), 29-32. DOI=10.5120/ijca2018917513

@article{ 10.5120/ijca2018917513,
author = { Akashdeep Dhiman, Dinesh Kumar },
title = { Sentiment Analysis Approach based N-gram and KNN Classifier },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 182 },
number = { 4 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 29-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number4/29752-2018917513/ },
doi = { 10.5120/ijca2018917513 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:10:23.525029+05:30
%A Akashdeep Dhiman
%A Dinesh Kumar
%T Sentiment Analysis Approach based N-gram and KNN Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 4
%P 29-32
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The sentiment analysis is the approach which is design to analysis positive, negative and neural aspects towards any approach. In the past years, many techniques are designed for the sentiment analysis of twitter data. Based on the previous study about sentiment analysis, novel approach is presented in this research paper for the sentiment analysis of twitter data. The proposed approach is the combination of feature extraction and classification techniques. The N-gram algorithm is applied for the feature extraction and KNN classifier is applied to classify input data into positive, negative and neural classes. To validate the proposed system, performance is analyzed in terms of precision, recall and accuracy. The experiments results of proposed system show that it performs well as compared to existing system which is based on SVM classifier.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment analysis Classifier SVM KNN

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