Twitter Sentiment Analysis using XGBoost and Logistic Regression: A Hybrid Approach
Ashwini M Joshi1 , Sameer Prabhune2
Section:Research Paper, Product Type: Journal Paper
Volume-7 ,
Issue-8 , Page no. 356-360, Aug-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i8.356360
Online published on Aug 31, 2019
Copyright © Ashwini M Joshi, Sameer Prabhune . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Ashwini M Joshi, Sameer Prabhune, “Twitter Sentiment Analysis using XGBoost and Logistic Regression: A Hybrid Approach,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.8, pp.356-360, 2019.
MLA Style Citation: Ashwini M Joshi, Sameer Prabhune "Twitter Sentiment Analysis using XGBoost and Logistic Regression: A Hybrid Approach." International Journal of Computer Sciences and Engineering 7.8 (2019): 356-360.
APA Style Citation: Ashwini M Joshi, Sameer Prabhune, (2019). Twitter Sentiment Analysis using XGBoost and Logistic Regression: A Hybrid Approach. International Journal of Computer Sciences and Engineering, 7(8), 356-360.
BibTex Style Citation:
@article{Joshi_2019,
author = {Ashwini M Joshi, Sameer Prabhune},
title = {Twitter Sentiment Analysis using XGBoost and Logistic Regression: A Hybrid Approach},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2019},
volume = {7},
Issue = {8},
month = {8},
year = {2019},
issn = {2347-2693},
pages = {356-360},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4836},
doi = {https://doi.org/10.26438/ijcse/v7i8.356360}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i8.356360}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4836
TI - Twitter Sentiment Analysis using XGBoost and Logistic Regression: A Hybrid Approach
T2 - International Journal of Computer Sciences and Engineering
AU - Ashwini M Joshi, Sameer Prabhune
PY - 2019
DA - 2019/08/31
PB - IJCSE, Indore, INDIA
SP - 356-360
IS - 8
VL - 7
SN - 2347-2693
ER -
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Abstract
World Wide Web is the largest source of information and huge information is available on the net. It is the growing tendency in users to express their opinions or thoughts using public opinion sites. Analysing all these opinions manually becomes challenging task so if we can develop the automated system to analyse what people want to say about any product, political party or any other thing it would be of great help. In this work we are trying to make readers life easier by providing the polarity of the reviews from user in automated way with better accuracy. The hybrid model is built using XGBoost and Logistic Regression classifiers and the performance of the hybrid model is compared to both the static models. As per expectation the hybrid model is performing better.
Key-Words / Index Term
XGBoost, Logistic Regression, Hybrid Model, Sentiment Analysis, Opinion Mining
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