Fakeheader: a tool to detect deceptive online news based on misleading news headlines and contents - Che Eembi @ Jamil, Normala; Ishak, Iskandar; Sidi, Fatimah; Affendey, Lilly Suriani (Ninety Nine Publication, 2021)
Online news has been the primary source of news content for newsreaders. Unfortunately, based on several findings, readers tend to judge on specific events based on the news headlines rather than its contents. With the advancement of mobile and web technologies, it is easier to spread the news to others with these unhealthy habits that can cause negative impacts on individuals, organizations, or nations that are victimized by the news. In the proposed work, a tool to detect deceptive news based on misleading headlines or content is developed. The tools incorporate data veracity framework for online news with Support Vector Machine and proposed combination of features. The experimental results show the proposed tool managed to produce high performance results with more than 90% precisions and recalls.