Fake News Classification on Twitter Using Flume, N-Gram Analysis, and Decision Tree Machine Learning Technique-Reference-Cited by-同舟云学术

Fake News Classification on Twitter Using Flume, N-Gram Analysis, and Decision Tree Machine Learning Technique

Published:2020 Issue: Volume: Page:139-147
ISSN:2524-7565
Container-title:Proceeding of International Conference on Computational Science and Applications
language:
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Author:

Keskar Devyani,Palwe Sushila,Gupta Ayushi

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-0790-8_15

Reference7 articles.

1. Horne BD, Adali S (2017) This just in: fake news packs a lot in title, uses simpler, repetitive content in text body, more similar to satire than real news. In: The 2nd international workshop on news and public opinion at ICWSM

2. Okoro EM, Abara BA, Umagba AO, Ajonye AA, Isa ZS (2018) A hybrid approach to fake news detection on social media. Nigerian J Technol (NIJOTECH) 37(2):454–462

3. Ahmed H, Traore I, Saad S (2017) Detection of online fake news using N-gram analysis and machine learning techniques. In: Conference paper (October 2017)

4. Wang WY (2017) Liar, Liar Pants on fire: a new Benchmark dataset for fake news detection. arXiv preprint arXiv:1705.00648

5. Rubin VL et al (2016) Fake news or truth? Using satirical cues to detect potentially misleading news. In: Proceedings of NAACL-HLT

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