ISSN2456-3315
Impact Factor10.57
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ESTD2016
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Paper Title
Sentiment Analysis on Covid-19 Impact using Python
Authors
Varada Lakshmi Soujanya , Samta Gajibhiye
Keywords
Sentiment analysis, python, covid-19, machine learning
Abstract
Coronavirus has represented a genuine pandemic danger the executives challenge as far as effect, readiness, reaction, and alleviation by governments, wellbeing associations, non-legislative associations (NGOs), broad communications, and partners. This investigation inspects the pandemic influenced hazard correspondence in questionable settings and its effect on the feelings and estimations got from the semantic examination in the public eye during the COVID-19 pandemic. This investigation inspects the pandemic influenced hazard correspondence in questionable settings and its effect on the feelings and estimations got from the semantic examination in the public eye during the COVID-19 pandemic. The flare-up of Covid sickness (COVID-19) overturned individuals' lives around the world. Coronavirus is brought about by serious intense respiratory disorder Covid 2 (SARS-CoV-2), a novel human microbe that virologists accept rose up out of bats and ultimately leaped to people through a delegate have. This flare-up has
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IJRTI — journal style
"Sentiment Analysis on Covid-19 Impact using Python", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.6, Issue 9, page no.117 - 123, September-2021, Available :https://ijrti.org/papers/IJRTI2109019.pdf
APA — 7th edition
Soujanya, V. L., & Gajibhiye, S. (2021). Sentiment Analysis on Covid-19 Impact using Python. International Journal for Research Trends and Innovation, 6(9), 117 - 123. https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019
MLA — 9th edition
Soujanya, Varada Lakshmi, and Samta Gajibhiye. "Sentiment Analysis on Covid-19 Impact using Python." International Journal for Research Trends and Innovation, vol. 6, no. 9, 2021, pp. 117 - 123, https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019.
Chicago — 17th, bibliography
Soujanya, Varada Lakshmi, and Samta Gajibhiye. "Sentiment Analysis on Covid-19 Impact using Python." International Journal for Research Trends and Innovation 6, no. 9 (2021): 117 - 123. https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019.
Harvard — author–date
Soujanya, V.L. and Gajibhiye, S. (2021) 'Sentiment Analysis on Covid-19 Impact using Python', International Journal for Research Trends and Innovation, 6(9), pp. 117 - 123. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019
IEEE — numbered reference
V. L. Soujanya and S. Gajibhiye, "Sentiment Analysis on Covid-19 Impact using Python," IJRTI, vol. 6, no. 9, pp. 117 - 123, Sep. 2021.
Vancouver — biomedical
Soujanya VL, Gajibhiye S. Sentiment Analysis on Covid-19 Impact using Python. IJRTI. 2021 Sep;6(9):117 - 123.
AMA — 11th edition
Soujanya VL, Gajibhiye S. Sentiment Analysis on Covid-19 Impact using Python. IJRTI. 2021;6(9):117 - 123. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2109019,
author = {Varada Lakshmi Soujanya and Samta Gajibhiye},
title = {Sentiment Analysis on Covid-19 Impact using Python},
journal = {International Journal for Research Trends and Innovation},
volume = {6},
number = {9},
pages = {117 - 123},
year = {2021},
month = {September},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Soujanya, Varada Lakshmi
AU - Gajibhiye, Samta
TI - Sentiment Analysis on Covid-19 Impact using Python
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 6
IS - 9
PY - 2021
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019
SP - 117
EP - 123
ER -
Issue
Volume 6 Issue 9,
September-2021
Pages : 117 - 123
Other Publication Details
Paper Reg. ID
IJRTI_181615
Published Paper ID
IJRTI2109019
Downloads
205,643
Research Area
Engineering
Country
bhilai, Chhattisgarh, India
Published
September 2021
Published Paper PDF
https://ijrti.org/papers/IJRTI2109019.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2109019
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
