مطالب

SUBJECT AND OBJECTIVES : Iran's 1979 Islamic Revolution, led by the Imam Khomeini, kicked off a new era in interaction between the clergy and the government; an interaction which has taken shape and been institutionalized at different levels of regulation, legislation and execution, and for sure within the framework of the views of the Leader of the Islamic Revolution and adopted laws. The Imam Khomeini's views about government-clergy interaction bears significance from two aspects; First and foremost, he was instrumental in the emergence of the Islamic Revolution and the ensuing establishment of the Islamic Republic, and also the stabilization of the role of leadership; Second, the criteria he has defined about clergy-government interaction could be an acceptable index for the assessment of their status quo. METHOD AND FINDING : The methodology of this article originally pursues an approach based on text analysis and hermeneutics although historical analysis is incorporated. For this reason, this article seeks to know the model of clergy-government interaction which is sketched out based on the Imam Khomeini's standpoint and specifically his 22-volume Sahifeh. The research hypothesis is that the model of clergy-government interaction preached by the Imam Khomeini relies on religious beliefs and the structure of an Islamic society with a view to monitoring the government and guiding people and making the life for its nation (Ommat) meaningful. CONCLUSION : The results of the research showed that this article highlights the Shia ideology before discussing the standing of the supreme authority on religious matters (Marja'), Shia political discourse and the process of its formation throughout different periods, as well as the new potentialities of the Islamic Revolution like institution of supreme clerical rule (Velayat-e Faqih) and religious democracy which is an influential factor in the formation and development of the Shia political discourse.

Social network research analyzes the relationships between interactions, people, organizations, and entities. With the developing reputation of social media, community detection is drawing the attention of researchers. The purpose of community detection is to divide social networks into groups. These communities are made of entities that are very closely related. Communities are defined as groups of nodes or summits that have strong relationships among themselves rather than between themselves. The clustering of social networks is important for revealing the basic structures of social networks and discovering the hyperlink of systems on human beings and their interactions. Social networks can be represented by graphs where users are shown with the nodes of the graph and the relationships between the users are shown with the edges. Communities are detected through clustering algorithms. In this paper, we proposed a new clustering algorithm that takes into account the extent of relationships among people. Outcomes from particular data suggest that taking into account the profundity of people-to-people relationships increases the correctness of the aggregation methods.