A Survey on Fake News Detection using Support Vector Model

Authors

  • Himani Kanojia  Computer Engineering Department, Government Engineering College Modasa, Gujarat, India
  • Prof. Rahul Vaza  Computer Engineering Department, Government Engineering College Modasa, Gujarat, India

DOI:

https://doi.org//10.32628/IJSRSET229225

Keywords:

Artificial Intelligence, Machine Learning, SVM, Text Classification, Sentiment Analysis

Abstract

In the boosting period of Social Media availability and easy availability of Internet to end users in various regions, many challenges are also occurred with usage of this technology. Fake news spreading in various field is also a major challenge in recent time. Fake news has been spreading into vast in significant numbers for various business reasons and also for political reasons. Problem of fake news has become frequent in the online world. People can get affected and their view are also affected easily by these type of fake news for its fabricated words. This type of news has enormous effects on the offline community in various sectors. In this way it is an interesting topic for research. Significant research has been conducted on the detection of fake news from English texts and other languages but there is chancel to improve the work with other languages as well as from multiple sources. Various algorithms like SVM and other supervised algorithm can be helpful to classify fake news. As Sentiment Score is an also a major point for detection of Fake news; in our work we are applying SVM algorithm with TF/IDF, multiple Languages (Language Conversation) etc.”

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2022-04-30

Issue

Volume 9, Issue 2, March-April-2022

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Himani Kanojia, Prof. Rahul Vaza, " A Survey on Fake News Detection using Support Vector Model, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 2, pp.125-131, March-April-2022. Available at doi : https://doi.org/10.32628/IJSRSET229225