Development of Big Data Strategy in Social Network Analysis toward Prediction of Crisis

Today , because of the complexities of cyberspace and its influence on many other fields from the national security viewpoint, the necessity of monitoring systems with cyberspace routing approach and also a global view of all its dimensions, including cultural, social, political, economic, security, military and science and technology seems more urging than ever. With the development of database systems and high volume data stored in these systems, there is a need for an instrument to process these stored data and information obtained from this process and aslo making them available to users. Ever increasing development of the communication tools in the field of information and communication technology, and the need to create intelligence dominance over this area toward prevention of surprises in crises encounterings, and considering the volume, velocity and variety of data in social networks, proves the neccessity for development of Big Data technology strategies in social network analysis. It is worth noting that this concept cannot in any way be dealt with traditional analytical methods and should modern technologies should be utilized instead. Since one of the main topics in the field of Big Data and data mining methods for remediation of achieving added value in the field is massive data, this study tries to identify the analysis and prioritization technologies needed to develop strategies of Big Data technology in social network analysis to predict the occurrence of crisis. According to the subject and objective of the study, type of applied-development research is used. The method of using quantitative methods and information gathering through a panel of experts and questionnaire fill-out, has been applied to a population of 20 elite students in the field of ICT and analysis utilizes big data strategy by means of Likert scale to evaluate priorities.