AUTOMATION OF ONLINE FAKE NEWS DETECTION SYSTEM IN SOCIAL MEDIA
The main thrust of this study is on automated fake news detection system in social media. Fake news has continued to grow both locally and globally due to the increase of Online Social Media web forums like Facebook, Twitter and blogging. This has been propelled even further by smartphones and mobile data penetration locally. This study provides a fake news digital forensics tool through the design, development and implementation of a software application. The objective of this study is to identify and analyze the different software techniques for fake news monitoring and provide the best suited and customized application. The study will develop an application using Linux Apache MySQL PHP and Python. The application will use Scrapy Python page ranking algorithm to perform web crawling and the data will be placed in a MySQL database for data mining. The application used Agile Software development methodology with twenty websites being the subject of interest. The websites will be the sample size to demonstrate how the application works together with the Python libraries as the framework for web crawling. MySQL data mining, database query application models will be used in performing the search of the lexicon of keywords for fake news, Inferences from the data mined from crawled web pages will be drawn using Microsoft Excel 2016. Excel will be used for data analysis with the data being presented in tables and figures.
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