Betweenness centrality measures the extent to which each node falls on the shortest path between other nodes (Freeman 1977). Nodes with high betweenness centrality are likely to be influential, since they are conduits through which information can be shared with otherwise unconnected nodes. Chat betweenness centrality: Each person’s betweenness centrality. Each document pools a single person’s messages to one channel in a 30-minute time period. In such cases, the two edges are collapsed into a single edge. But, for the purpose of clustering, this resulted in almost every observation being categorized with a single dominant topic. This belief had some merit, but with hindsight and further observation I have realized that some of the errors I encountered with other clients also occurred with Monocle, yet resulted in a more graceful failure. Each observation under this analysis represents one users’ activity over a time period of one month. Second, I created a cluster that classified each users’ activity on GitHub over each month. Next, an agglomerative (bottom-up) hierarchical cluster analysis was used to identify roles of IndieWeb contributors each month based on the topics they discussed in chat and the types of activities they engaged in on GitHub.
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