GSA Annual Meeting in Denver, Colorado, USA - 2016

Paper No. 255-5
Presentation Time: 9:00 AM-6:30 PM

MINERAL ECOLOGY: SOCIAL NETWORK ANALYSIS AND SOCIOGRAMS OF MINERAL CONNECTIONS, DISTRIBUTIONS, AND SEGMENTATION


MORRISON, Shaunna M.1, DOWNS, Robert T.1, GOLDEN, Joshua J.1, PIRES, Alexander J.2, FOX, Peter3, MA, Xiaogang4, ZEDNIK, Stephan3, ELEISH, Ahmed3, KOLANKOWSKI, Sophia3, LIU, Chao5, HUMMER, Daniel5, MEYER, Michael5, RALPH, Jolyon6, HYSTAD, Grethe7 and HAZEN, Robert M.8, (1)Geosciences, University of Arizona, 209 Gould-Simpson Building, Arizona, AZ 85721-0077, (2)Department of Geosciences, University of Arizona, Tucson, AZ 85721, (3)Earth and Environmental Science, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY 12180, (4)Department of Computer Science, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY 12180, (5)Geophysical Laboratory, Carnegie Institution of Science, 5251 Broad Branch Rd. NW, Washington, DC, DC 20015, (6)mindat.org, Surrey, CR4 4FD, United Kingdom, (7)Department of Mathematics, Computer Science, and Statistics, Purdue University Northwest, Hammond, IN 46323, (8)Geophysical Laboratory, Carnegie Institution for Science, Washington, DC 20015, shaunnamm@email.arizona.edu

Large databases of mineral species (rruff.info/ima) and their localities (mindat.org) reveal patterns of mineral coexistence and geographical distribution that mimic social networks, as commonly applied to such varied topics as social media interactions, research collaborations, global terrorism, and disease transmission. We apply social network analysis (SNA) to Earth’s most common mineral species, including rock-forming minerals and ore minerals, which display patterns that are remarkably similar to those of some human social networks. We present a variety of sociograms, for which “nodes” represent individual mineral species and “ties” represent co-existing species. These powerful visualization techniques reveal parallels to such SNA metrics as connectivity (i.e., the extent to which two mineral species occur together), homophily (the tendency of some mineral species to occur with other similar species), network openness versus closure (the extent to which certain key mineral species “anchor” networks of mineral subsets), and segmentation (i.e., development of isolated clusters or “cliques” of mineral species). SNA of minerals presents promising avenues for discovering previously hidden trends in mineral diversity-distribution systematics, as well as providing new pedagogical approaches to teaching petrology and ore deposit geology. Note that this poster will be accompanied by real-time laptop demonstrations of SNA and dynamic sociograms.