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Journals / International Advanced Researches and Engineering Journal / 2021 / Cilt: 5 - Sayı: 1

Analysis of whether news on the Internet is real or fake by using deep learning methods and the TF-IDF algorithm

Tilbe KORKMAZ
Ali ÇETİNKAYA
Hakan AYDIN
Mehmet Ali BARIŞKAN
Pages
31–41
Publication Date
2022-10-19
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The classification was made with the data set used and 93.88% success and 6.12% error were obtained as a result of the analysis.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Internet use has become increasingly widespread nowadays.
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Key Findings & Data:In addition, there is a significant increase in the amount of text content produced in digital media.
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Conclusion & Impact:The classification was made with the data set used and 93.88% success and 6.12% error were obtained as a result of the analysis.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Natural Language Processing · Text Analysis · Text Classification

Abstract

Internet use has become increasingly widespread nowadays. In addition, there is a significant increase in the amount of text content produced in digital media. However, the accuracy and inaccuracy of the news we read and the content produced in a large number are also unknown. In this study, classification and analysis of whether the news is real or not were done by using Deep Learning methods. For the English news, the data set created by Katharine Jarmul was used. The data set contained a total of 6336 news items. The distribution of this data set, which consisted of political and political news, was 50% fake and 50% real. The method used in text classification was Term Frequency - Inverse Document Frequency (TF-IDF). The classification was made with the data set used and 93.88% success and 6.12% error were obtained as a result of the analysis.

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Cite This Article

KORKMAZ, T., ÇETİNKAYA, A., AYDIN, H., BARIŞKAN, M. A. (2022). Analysis of whether news on the Internet is real or fake by using deep learning methods and the TF-IDF algorithm. International Advanced Researches and Engineering Journal, Cilt: 5 - Sayı: 1, 31–41. https://ajindex.com/articles/539291

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