Towards A Headline-based Deception Detection Approach for Data Veracity in Online Digital News

Authors

  • Normala Che Eembi @ Jamil Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
  • Iskandar Ishak Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
  • Fatimah Sidi Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
  • Lilly Suriani Affendey Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia

Keywords:

Headlines, Deception, Online News, Framework,

Abstract

Since its existence in 1990's, online news has been the major source of news content for news readers. Unfortunately, based on a number of findings, readers tend to judge on certain event based on the news headlines rather than its contents. With the advancement of mobile and web technologies, it is easier to spread news to others and this unhealthy habits can cause negative impacts towards individuals, organizations or nations that are victimized by the news. This paper proposes a framework to detect deceptive online news based on the news headlines. By having an accurate detection upon deceptive news based on its content, it can assist readers to identify misleading news and to help them to find relevant news for their source of information.

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Published

2017-09-15

How to Cite

Che Eembi @ Jamil, N., Ishak, I., Sidi, F., & Affendey, L. S. (2017). Towards A Headline-based Deception Detection Approach for Data Veracity in Online Digital News. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-11), 33–37. Retrieved from https://jtec.utem.edu.my/jtec/article/view/2734

Issue

Vol. 9 No. 2-11: The Challenge of Computer and Engineering in Building Sustainable Service Systems I

Section

Articles

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)