UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 5
May-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

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Published Paper ID:
JETIR2105659


Registration ID:
309715

Page Number

e951-e958

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Title

Social Media a Boon: Pirate News Identification Using Knowledge Engineering

Authors

Abstract

The typical news use through non-traditional sources, for instance, online life, web diaries and messaging bundles have definitely expanded a lot of excitement for the on-going time. One of the rule wellsprings of information content that people depend these days upon is through electronic interpersonal interaction. The climb of online informal communication as a news source has the issue old enough and expansive of misshaped information. This addresses a peril not only express to a phase in which the news content is dispersed at this point furthermore to the internet mode for giving news with everything taken into account. The assignment, we endeavoring to carry out an enterprising methodology to expect pirate information that inescapable in web based systems administration. With the improvement of information and advancement has immediately extended the general population with admittance to the web, which has changed the course for correspondence, exchanging and consuming information. Along these lines, the concern of pirate news has become a huge to the overall population. As all of them relies more upon online structures association now-a-days for information or news. With the improvement of online facility as a phase for spread and getting news from various sources is critical yet additionally clearly has an issue of passing on and getting out counterfeit word. The problematic assertion can be imparted as: Design and improvement of an application which coordinates the news and predicts the level of exactness.

Key Words

Fake News, Degree of Correctness, Probability, Classification, Web, Support Vector Machine (SVM), Linear Regression, Naïve Bayes, Vectorization.

Cite This Article

"Social Media a Boon: Pirate News Identification Using Knowledge Engineering", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.e951-e958, May-2021, Available :http://www.jetir.org/papers/JETIR2105659.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Social Media a Boon: Pirate News Identification Using Knowledge Engineering", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppe951-e958, May-2021, Available at : http://www.jetir.org/papers/JETIR2105659.pdf

Publication Details

Published Paper ID: JETIR2105659
Registration ID: 309715
Published In: Volume 8 | Issue 5 | Year May-2021
DOI (Digital Object Identifier):
Page No: e951-e958
Country: Tumkur, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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