2018
Okoro, Abara; Isa Umagba, Anyalewa
A HYBRID APPROACH TO FAKE NEWS Conference
2018.
@conference{Author2023,
title = {A HYBRID APPROACH TO FAKE NEWS},
author = {Okoro, Abara and Umagba, Isa, Anyalewa
},
url = {https://nict.edu.ng/wp-content/uploads/2023/11/A-HYBRID-APPROACH-TO-FAKE-NEWS-Zayyad-Isa.pdf},
year = {2018},
date = {2018-04-01},
urldate = {2018-04-01},
abstract = {Fake news has grown tremendously in recent times and this growth has had a great impact on how we make a number of sensitive decisions daily including becomes our President. There have been a wide range of solutions developed to help humans distinguish between fake and real news however, the solutions rely on either a machine-based approach or a human-based approach to detection. Research in the fields of computer science, artificial intelligence and psychology research has shown the limitations in both approaches. Based on these research findings, this paper proposes a hybrid model for detecting fake news on social media using a combination of both the human-based and machine-based detection approaches.
},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Fake news has grown tremendously in recent times and this growth has had a great impact on how we make a number of sensitive decisions daily including becomes our President. There have been a wide range of solutions developed to help humans distinguish between fake and real news however, the solutions rely on either a machine-based approach or a human-based approach to detection. Research in the fields of computer science, artificial intelligence and psychology research has shown the limitations in both approaches. Based on these research findings, this paper proposes a hybrid model for detecting fake news on social media using a combination of both the human-based and machine-based detection approaches.