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  Published Paper Details:

  Paper Title

FAKE NEWS CLASSIFICATION

  Authors

  Pratibha Patil,  Sitaram Longani,  Anil Kumar Jakkani

  Keywords

Logistic Regression, Multinomial Naive Bayes, Random Forest Support Vector Machine& XGBoost

  Abstract


Fake news can be interpreted as falsified information or wrong facts presented in the newspapers, television news, online media with a spiteful intent to damage the reputation of a person, organization or any other society for personal or professional benefits. Few media outlets present incorrect narrative about prominent personalities to gain Television Rating Points (TRP's), to increase viewership to yield higher revenue, to smear a person to settle previous conflicts etc. Given the serious consequences that result a fake news article and its impact on formulations of key decisions in everyday life, it is necessary to come up with a resolution plan to stop the spread of fake news and handle it in a suitable manner. In this project, we try to resolve the problem of fake news by utilizing Natural Language Processing (NLP) which is a Data Science sub-branch to come up with a solution that can be used to classify the fake news.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTY020011

  Paper ID - 244439

  Page Number(s) - 60-68

  Pubished in - Volume 9 | Issue 5 | May 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Pratibha Patil,  Sitaram Longani,  Anil Kumar Jakkani,   "FAKE NEWS CLASSIFICATION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 5, pp.60-68, May 2021, Available at :http://www.ijcrt.org/papers/IJCRTY020011.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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