# Knowledge Sharing in Security-Sensitive Communities
## 6 Discussion
However, as participants gain experience, they rely more on expertise similarity and less on categorical attributes like location or status [87]. Factors influencing knowledge sharing in professional virtual communities include reciprocity norms, interpersonal trust, self-efficacy, and perceived advantages [88]. We examined the relationship between network metrics, trust, homogeneity between members, the number of organizations participating in the observed discussion, and knowledge sharing. We divided network metrics into the spread of knowledge and communication levels. The spread of knowledge allows knowledge-sharing analysis across the entire network. Measures of the spread of knowledge include network radius, diameter, and density. Results indicate that when the goal is operational tasks, the radius and diameter are smaller than in non-sensitive organizations. In addition, density in a security-sensitive organization is higher than in a non-sensitive organization. The level of communication allows the analysis of network parts, such as pairs of vertices, triads, neighbors, and clusters. Network metrics that reflect communication include reciprocity and transitivity. Intelligence organizations operate under constraints, rules, procedures, and norms that impact the behavior of the network and the sharing of knowledge in the community. Communication patterns affect the conversation. For example, participants who are soldiers may only participate in the conversation when their commander is present. However, if the goal of the groups created were to transfer knowledge through a trust-based dialogue, we would expect to see a development of collective intelligence even when civil intelligence joins the group, whose goal is the same--the protection of citizens. Our results show that the intelligence communities are denser than other networks tested. On the one hand, when trust develops within networks, it fosters interactions and collaborations, which enable knowledge sharing and the development of collaborative intelligence. On the other hand, inhibiting factors such as lack of control over the flow of data and organizational culture hinder the sharing of knowledge due to security considerations. In traditional SNA theories, these factors are not considered. In conventional research that analyzes social networks, it is common to analyze different communities in terms of age, size, gender, and different natures or goals of the organizations being examined. However, the present study is unique in analyzing and comparing the unique intelligence community with civilian communities. This study also examined the effect of connecting two security-sensitive organizations, one military and one civilian, on knowledge sharing. The results indicate that when these two organizations participate together in the same group, there is a decrease in knowledge sharing--in the reciprocity of reactions, transitivity, and the density of the network. When comparing the network structures created by the security-sensitive organizations and non-sensitive organizations, statistically significant differences were found. Moreover, it can be understood that structure affects behavior, and vice versa, the behavior of the participants, their organizational culture, unique education in the intelligence division, etc., produce a defined structure.