Partitioning Multimode Networks

Most networks examined so far involve connections between nodes all of the same type, known as one‐mode networks. This chapter examines partitioning and clustering in multimode network data. A number of techniques have been developed for dealing with non‐binary data or more precisely non‐network type data. The chapter first concentrates on two mode datasets and then discusses general multimode approaches. In considering two‐mode networks the authors consider the problem of partitioning both modes to find sets of actors and events. For single‐mode networks the most commonly used and accepted technique is Newman's community detection, which optimizes modularity. M. J. Barber extended modularity to two‐mode data and developed an algorithm specifically for this type of data.