2011/04/30 by Steve Gregory, Steven Gregory · 1 citation
Computer Science · Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #Computer science #Evolutionary Game Theory and Cooperation #Opinion Dynamics and Social Influence #cs.SI #physics.soc-ph
paper · pdf · doi:10.1016/j.physa.2011.12.025
published as Physica A 391 (2012) 2752-2763 · This is an extended preprint version that includes an extra example: the college football network as an ordered (spatial) network. Further improvements, not included here, appear in the journal version. Original title changed (from "Ordered and continuous community structure in networks") to match journal version
openalex publication_date 2011/12/21 · arxiv created 2012/02/13 · arxiv updated 2012/02/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Community structure in networks is often a consequence of homophily, or assortative mixing, based on some attribute of the vertices. For example, researchers may be grouped into communities corresponding to their research topic. This is possible if vertex attributes have discrete values, but many networks exhibit assortative mixing by some continuous-valued attribute, such as age or geographical location. In such cases, no discrete communities can be identified. We consider how the notion of community structure can be generalized to networks that are based on continuous-valued attributes: in general, a network may contain discrete communities which are ordered according to their attribute values. We propose a method of generating synthetic ordered networks and investigate the effect of ordered community structure on the spread of infectious diseases. We also show that community detection algorithms fail to recover community structure in ordered networks, and evaluate an alternative method using a layout algorithm to recover the ordering.