Designing an early warning model in social media surveillance

The impact of cyberspace on human life and the employment of the obtained big data in all social, political, and security aspects of society are among the global trends. The present study seeks to answer the question concerning how governments can become aware of the trend of sensitive issues, which can result in crises, and plan against them using the big data of social media. The goal is to define an early warning system (EWS) architecture in the observation of social media for the early detection of the signals of sensitive and critical issues and assess them. Given the importance of such a system, which is among the governance requirements in the current century, along with its security sensitivities for pioneering countries, no clear information about the architecture of similar examples is available. Thus, creating such a system requires designing from scratch. Accordingly, in the present study, by taking advantage of multi-grounded theory, the early warning system's model is identified. The model is validated through fuzzy Delphi, which approves the proposed model for EWS.