| Title |
A machine learning technique for detection of social media fake news / |
| Authors |
Arowolo, Micheal Olaolu ; Misra, Sanjay ; Ogundokun, Roseline Oluwaseun |
| DOI |
10.4018/IJSWIS.326120 |
| Full Text |
|
| Is Part of |
International journal on semantic web and information systems.. Hershey, PA : IGI Global. 2023, vol. 19, iss. 1, p. 1-25.. ISSN 1552-6283. eISSN 1552-6291 |
| Keywords [eng] |
detection techniques ; fake news ; machine learning ; social media ; social network |
| Abstract [eng] |
The emergence of the Internet and the growing development of online platforms (like Facebook and Instagram) opened the way for disseminating information that hasn’t been experienced in the history of mankind earlier. Consumers generate and share more information and a massive amount of data than ever with the growing utilization of social media sites, many of which are deceptive with little relevance to reality. A daunting task is the automated classification of a text article as misleading or misinformation. To see the latest news alerts, individuals often utilize e-newspapers, Twitter, Instagram, Youtube, and many more. Fake news created on social media can lead to uncertainty amongst individuals and psychiatric illness. We may detect that news obtained based on machine learning techniques is either true or false. This study proposes a machine learning technique to detect fake news by carrying out filtration on social media data, classifying the preprocessed data using a machine learning algorithm, evaluating the developed system, and evaluating the results. |
| Published |
Hershey, PA : IGI Global |
| Type |
Journal article |
| Language |
English |
| Publication date |
2023 |
| CC license |
|
