Wil M. P. van der Aalst; Vladimir Batagelj; Goran Glavaš; Dmitry I. Ignatov; Michael Khachay; Sergei O. Kuznetsov; Koltsov Springer Nature Switzerland AG (2018) Pehmeäkantinen kirja
Wil M. P. van der Aalst; Vladimir Batagelj; Dmitry I. Ignatov; Michael Khachay; Valentina Kuskova; Andrey Kutuzov; Kuznets Springer Nature Switzerland AG (2019) Pehmeäkantinen kirja
Wil M. P. van der Aalst (ed.); Vladimir Batagelj (ed.); Dmitry I. Ignatov (ed.); Michael Khachay (ed.); Valentina ( Kuskova Springer (2020) Pehmeäkantinen kirja
Wil M. P. van der Aalst (ed.); Vladimir Batagelj (ed.); Alexey Buzmakov (ed.); Dmitry I. Ignatov (ed.); Anna (ed. Kalenkova Springer (2021) Pehmeäkantinen kirja
Wil M. P. van der Aalst; Vladimir Batagelj; Dmitry I. Ignatov; Michael Khachay; Olessia Koltsova; Andrey Kutuzov; Kuznetso Springer Nature Switzerland AG (2021) Pehmeäkantinen kirja
This book provides an integrated treatment of blockmodeling, the most frequently used technique in social network analysis. It secures its mathematical foundations and then generalizes blockmodeling for the analysis of many types of network structures. Examples are used throughout the text and include small group structures, little league baseball teams, intra-organizational networks, inter-organizational networks, baboon grooming networks, marriage ties of noble families, trust networks, signed networks, Supreme Court decisions, journal citation networks, and alliance networks. Also provided is an integrated treatment of algebraic and graph theoretic concepts for network analysis and a broad introduction to cluster analysis. These formal ideas are the foundations for the authors' proposal for direct optimizational approaches to blockmodeling which yield blockmodels that best fit the data, a measure of fit that is integral to the establishment of blockmodels, and creates the potential for many generalizations and a deductive use of blockmodeling.
