other hand, if we have a network that is small world, that is, a network in which the shortest path between two randomly chosen nodes is much smaller than that one would expect, we can expect the rumor spread far away. Also we can compute the final number of people who once spread the news, this is given by In networks the process that does not have a threshold in a well mixed population, exhibits a clear cut phase-transition in small worlds. The following graph illustrates the asymptotic value of as a function of the rewiring probability . Microscopic models The microscopic approaches attracted more attention in the individual's interaction: "who influenced whom." The known models in this category are the information cascade and the linear threshold models, the energy model, HISBmodel and Galam's Model. Independent cascades models Linear threshold models Energy model HISBmodel model The HISBmodel is a rumor propagation model that can reproduce a trend of this phenomenon and provide indicators to assess the impact of the rumor to effectively understand the diffusion process and reduce its influence. The variety that exists in human nature makes their decision-making ability pertaining to spreading information unpredictable, which is the primary challenge to model such a complex phenomenon. Hence, this model considers the impact of human individual and social behaviors in the spreading process of the rumors. The HISBmodel proposes an approach that is parallel to other models in the literature and concerned more with how individuals spread rumors. Therefore, it try to understand the behavior of individuals, as well as their social interactions in OSNs, and highlight their impact on the dissemination of rumors. Thus, the model, attempts to answer the following question: ``When does an individual spread a rumor? When does an individual accept rumors? In which OSN does this individual spread the rumors?''. First, it proposes a formulation of individual behavior towards a rumor analog to damped harmonic motion, which incorporates the opinions of individuals in the propagation process. Furthermore, it establishes rules of rumor transmission between individuals. As a result, it presents the HISBmodel propagation process, where new metrics are introduced to accurately assess the impact of a rumor spreading through OSNs. References Social networks