know about the network characteristics of the respondents' farmers inside an innovation adoption network, and to identify the relationship between their network characteristics and the time of adoption of this innovation. Data were collected from all farmers of one of the villages of Assiut governorate by questionnaire. The study used UCINET software to analyze and visualize the data. The results identified the farmers with the best network characteristics among farmers in the whole network. Social network analysis states that we can rely on them to convince the largest number of farmers to adopt the innovation very rapidly with the shortest links. Also it cleared up that there's a positive significance correlation between the time of adoption of the innovation and these variables: degree of reach, out-geodesic distances and efficiency of ego network. On the other hand, it came to clear that there's a negative significance correlation between the time of adoption of the innovation and these variables: number of directed ties, density of ego network, two-step reach and closeness centrality.