Spontaneity of Interaction in a Social Network

Social interaction plays an important role for the development of social capital in many dynamic networks. These interactions may not be secure from self-interested agents. For that, each agent must be capable to identify reliable interaction allies. In light of this, the focus is on developing a different type of interactions among the agents inside a spontaneous networked organization (SNO). It helps to overcome such a problem through applying a broad range of service level agreements (SLAs). We will present a policy of negotiation and renegotiation to accelerate the execution process of the fittest task provided by the organized agent. Moreover, by applying collaborative filtering (CF), we will examine a different type of data to illustrate how agents interact implicitly or explicitly and how these interactions affect the social capital. This method obtains a high performance of interaction and can help to control the spontaneous flow of behaviors and knowledge to be more accurate when agents communicate rationally since trust is recorded in such a distributed organization.