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Methods for the Measurement and Visualization of Social Networks in Multi-User Virtual Worlds Marc Smith has also investigated the social life of small graphical chat spaces by analyzing Microsoft's V-Chat systems (Smith, Farnham, and Drucker, 2000). The VChat research illustrates the usage patterns of graphical chat systems, illumi- nating the ways physical proxemics are translated into social interactions in online environments. Krikorian, Lee, Chock, and Harms (2000) devel- oped methods to study user proximity in graphi- cal chat rooms, and found that various perceived demographics influenced the social "distance" of avatars in the graphical chat environment. In addition to the structural analysis performed in the research discussed above, there have also been a number of methodological advancements regarding the communicative content of online communities. Sack (2000) generated conversa- tion maps of newsgroup postings, and was able to explain what very large conversations look like by visualizing large amounts of interaction in a gap in procedures to extract structural social networks from IRC. Many of the parallel online community (e.g. Usenet) and social media (e.g. social networking sites) research streams have benefited from structural analysis and social network representation, but interaction via IRC is still one of the most common forms of interac- tion in a variety of contexts (i.e. online gaming, educational environments), yet the structure still remains cloaked behind the form of log file data used to store IRC. Understanding the structure of the interaction provides an in-depth and unique window into MUVWs along several lines. First, network position can be used to identify network roles such as, similar to Turner et al. (2006) iden- tifying roles such as answer person and question person. Second, network analytic techniques can be employed in the subsequent data, such as cen- trality and tie strength, discussed above. Finally, network visualizations can be generated allowing