Abstract
The dissemination of fake information through social media has several harmful effects on the social life of a nation. Indonesia has been afflicted by the dissemination of erroneous information regarding the negative health consequences of vaccination, resulting in widespread unwillingness to undergo immunization. Therefore, it is necessary to combat such misleading information. We developed a web application using machine learning technologies to identify bogus information flowing on Indonesian Twitter. A Passive-Aggressive Classifier and n-gram tokenization are used to handle data. The application test results indicate that the detection accuracy, precision, and recall for 1-3 grams of tokenization are higher than 90%. In addition, the black box approach yields reliable findings for all application functionalities.
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.
