Keywords
community finding, networks, link analysis
Disciplines
Social Statistics
Abstract
Networks often exhibit community structure and there are many algorithms that have been proposed to detect the communities. Different sets of communities have different characteristics. Community finding algorithms that are designed to optimize a single statistic tend to detect communities with a narrow set of characteristics. In this paper, we present evidence for the differences in community characteristics. In addition, we present two new community finding algorithms that allow analysts to find community sets that are not only high quality but also germane to the characteristics that are desired.
Original Citation
Scripps, J., Trefftz, C., & Kurmas, Z. (2018). The difference between optimal and germane communities. Social Network Analysis and Mining, 8(1). https://doi.org/10.1007/s13278-018-0522-1
ScholarWorks Citation
Scripps, Jerry; Trefftz, Christian; and Kurmas, Dr. Zachary, "The Difference between Optimal and Germane Communities" (2018). Funded Articles. 109.
https://scholarworks.gvsu.edu/oapsf_articles/109
