This research aims to study the relationships of social network and migration of students among different regions. Excluding attested factors such as gender, age, education, and income, this research seeks to answer whether different social networks have an influence on migration of students who studied in a secondary school outside the community. Taking advantage of longitudinal data from Kanchanaburi Demographic Surveillance System (KDSS) in 2000 and 2004, thirty-five communities in four districts were examined through the Social Network Analysis. An essential pattern emerged. The secondary education was structured under the ‘tree net’ pattern which reflected students’ distribution around their communities. As there were many who studied in the neighboring communities, all focused districts posses their own centralization. This finding proves that good schools are not merely clustered in the urban areas. They are, however, equally spread to outer areas. This pattern diminishes migration flow of the rural students to the big cities as well as saving the travel cost which would have occurred from long-distance commuting. It is found that the social networks factor of eigenvector has a statistically significant positive effect on migration. The results suggest that the public sector should allow the social network to be strong so that exchange of information or needs assistance with migration becomes easier.