Sunbelt XXXI International Network for Social Network ... - INSNA

Are You Getting What You Came For? Evolutionary Mechanisms In Online Social Support CommunitiesChewning, Lisa V.Online Social NetworksSocial Support, On‐line Communities, Social Networks On The Web, Social Network, EvolutionTHURS.AM1Online communities, like in‐person communities, provide support, information, and social capital to members. Unlike in‐person communities, onlinecommunities are not geographically bound, and can be social networks of individuals bound by common interests or needs (Wellman, 1997). Thus, onlinecommunities can provide a venue through which individuals can establish networks of social support, or “relationships that provide individuals with actualassistance or that embed individuals within a social system believed to provide love, caring, or sense of attachment to a valued social group” (Hobfoll, 1988, p.121). Previous research (Monge, Heiss, & Margolin, 2008) has studied network evolution in terms of the interaction of populations and the overallenvironment as populations within a community compete for resources. However, as the incentive to join online communities, as well as the parameters of theenvironment, differ from in‐person communities, the evolution of online community networks may differ from those of in‐person communities. Thus, thispaper seeks to understand the mechanisms behind the organization and evolution of social networks in online communities. This paper analyzes the evolutionof an online community for parents of children with disabilities over a one‐year period. By tracking the interaction of community members created bycommenting on individual threads, this paper provides longitudinal data detailing the evolution of the network structure. Conclusions from the data willfurther understandings of both social support networks and network evolution in online platforms.Assessment Of Centrality Measure Across Social Network SoftwareWang, YuFei; Murphy, Philip J.; T.Cuenco, KarenCentrality Measures in Social NetworksMethods, Software, CentralityWED.PM1Social network analysis software development has been increasing and so has the range of analyses that are available. Because no one program incorporatesthe full range of analytic approaches, a common solution is to use two or more software packages to address a given analytic need. In the process, basicnetwork measures may be generated through different platforms that vary in their calculations. Careful checking and comparison of these software outcomeshas not been conducted systematically and leaves the analyst vulnerable to discrepancies that affect inference and propagate erroneous conclusions . Tounderstand the magnitude and character of variability present among these network packages, we examine the most basic building‐blocks of algorithms innetwork analysis: measures of centrality. Specifically, we are interested in how and in what ways (normalized) degree, closeness, betweenness, andeigenvector centralities and their variants correlate or covary between programs. These measures are assessed using both one‐mode and two‐mode networkbiologic data across eight popular analysis software, including Pajek, ORA, UCINET, igraph, and others. Time permitting, we also assess global measures such asclusterability and the impact of centrality variation on subsequent community structure algorithms, when available. With this research, we characterize theissues that are introduced when we move our analytic work from program to program.