Abstract
The Internet has in recent years become a mainstream medium for sharing news and disseminating information. Some news websites use clickbait to earn advertising revenue by deceiving users to click news links. Clickbait is used as part of a disinformation strategy to attract users to click article links in order to obtain advertising revenue or spread false information. Clickbait not only affects the reading experience but also encourages the spread of disinformation or misinformation. This article proposes a clickbait news detection system that is based on artificial intelligence and feature engineering. The system has modules for data collection, text preprocessing, feature extraction, feature evaluation, model training, and prediction. The feature extraction and evaluation modules are based on 18 lexicon-based or format-based features. The proposed system is 98.42% accurate in validating a training dataset, representing 10.75% higher accuracy in detecting clickbait news than other systems.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
