While the digital environment, and in particular social media, surrounds not only human's identity and its societal functions projection, e.g., institutional and financial aspects, it also captures both individual and collective thoughts regarding former, ongoing, and future concepts, trends, and incidents placed in the physical world, in the digital environment, or in both which could impact both individual and collective consciousness, behaviour, and attitude towards different dimensions of reality. Accordingly, an initial attempt to define and model responsible digital security behaviour was made and ongoing discourses and AI-based solutions for tackling and containing social manipulation mechanisms exist in this domain. Noteworthily is that dedicated attention to understanding and modelling responsible digital security behaviour in social media for tackling and/or countering social media manipulation, e.g., disinformation and misinformation, still lacks. To this end, this research aims (i) to capture the factors influencing user behaviour towards tackling and/or countering social media manipulation, (ii) to build a Machine Learning model that assesses user's responsibility in relation to tackling and/or countering social media manipulation mechanisms, and (iii) propose a set of socio-technical recommendations for building resilience to such mechanisms. To accomplish these research objectives, a Design Science Research methodological approach is taken by designing, developing, and evaluating the model proposed through exemplification. Finally, this research aims to enhance digital security awareness and resilience to social media manipulation of users and policy decision-makers to manage and further extend in a responsible and safe way the digital environment.