Statistical analysis of network data--an application to diffusion of innovation Export

@article{Nyblom:2003, abstract = {General methodology is developed here to deal with the association between a a binary variable and network connections with or without confounding covariates. Also the case when the network is observed at several time periods is treated. As an application we consider the diffusion of organic farming in the province of North Karelia in Finland. It turns out that organic farms are more clustered than would be expected under pure random allocation. The neighborhood effect remains when adjusting for the production lines of the farms. The spatio-temporal analysis shows that new adopters are more often found within the neighborhoods of each others and of earlier adopters.}, author = {Nyblom, Jukka and Borgatti, Steve and Roslakka, Juha and Salo, Mikko A.}, citeulike-article-id = {3177089}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/S0378-8733(02)00050-3}, citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/B6VD1-47T2F85-2/2/e533a86b8df77bb64375e20b7c507100}, doi = {10.1016/S0378-8733(02)00050-3}, journal = {Social Networks}, keywords = {diffusion, empirical, innovation, longitudinal, network}, month = {May}, number = {2}, pages = {175--195}, posted-at = {2008-08-31 21:44:34}, priority = {2}, title = {Statistical analysis of network data--an application to diffusion of innovation}, url = {http://dx.doi.org/10.1016/S0378-8733(02)00050-3}, volume = {25}, year = {2003} }

TY - JOUR ID - Nyblom:2003 L3 - citeulike-article-id:3177089 N2 - General methodology is developed here to deal with the association between a a binary variable and network connections with or without confounding covariates. Also the case when the network is observed at several time periods is treated. As an application we consider the diffusion of organic farming in the province of North Karelia in Finland. It turns out that organic farms are more clustered than would be expected under pure random allocation. The neighborhood effect remains when adjusting for the production lines of the farms. The spatio-temporal analysis shows that new adopters are more often found within the neighborhoods of each others and of earlier adopters. IS - 2 JF - Social Networks EP - 195 TI - Statistical analysis of network data--an application to diffusion of innovation VL - 25 SP - 175 KW - diffusion KW - empirical KW - innovation KW - longitudinal KW - network AU - Nyblom, Jukka AU - Borgatti, Steve AU - Roslakka, Juha AU - Salo, Mikko PY - 2003/05// UR - http://dx.doi.org/10.1016/S0378-8733(02)00050-3 ER -