Social Media Manipulation Awareness through Deep Learning based Disinformation Generation

As a digital environment introduced for establishing and enhancing human communication through different social networks channels, media continued to develop spread at an incredible rate making it difficult find or imagine concept, technology, business that does not have plan its representation space. Concurrently, became playground even battlefield where ideas carrying out diverse validity degrees are reaching their target audiences generated by clear trustable well-known, uncertain, evil aimed entities. In the stride carried preventing, containing, limiting effects of manipulation last two types entities, proper/effective security awareness is critical mandatory in first place. On this behalf, several strategies, policies, methods, technologies were proposed research practitioner communities, but such initiatives take mostly defender perspective, enough cyberspace offender advantage attack. Therefore, aims produce taking stance generating analysing disinformation tweets using deep learning. To reach goal, Design Science Research methodology followed Data approach, results obtained analysed positioned ongoing discourses showing effectiveness approach role building future detection solutions. This also intends contribute design further transparent responsible modelling gaming solutions building/enhancing definition realistic cyber/information operations scenarios dedicated/engaging large multi-domain (non)expert audiences.