https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=117855 According to Smith et al.’s finding, the “Comic_Con” graph has a structure of Brand Clusters. As we can see from the graph, 5,606 Twitter users who tweeted about "Comic_Con" formed different small-sized subgroups. The users shown in this figure don’t follow or directly reply to or mention other users who... More
When wanting to look at social networks for specific fandoms, I think the context of a more significant event and a broader culture are needed for context. To see this context we will start by examining a social networking graph that represents the recent New York Comic-Con as a whole. More
Smith, Rainie, Sheneiderman, and Himelboim (2014) identified six distinct types of community clusters on Twitter: Polarized Crowd, Tight Crowd, Brand Clusters, Community Clusters, Broadcast Network and Support Network. I am going to discuss examples of Broadcast Network and Tight Crowd through analysis of communities using #AdWeek (Broadcast Network) and #SFCyberSecurity... More
The rise of social networking sites, the Internet, and mobile computing have ushered in a new era of social organization and interaction. This three-pronged change, dubbed the Triple Revolution by Rainie and Wellman (2012), has “made possible the new social operating system… call[ed] ‘networked individualism’” (p. 12). The characteristic features... More
In the article Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters, Smith and his colleagues observed and concluded six structures of network types based on the conversations on Twitter. However, what is the factor causes the different shape of the network communities? Infomediation, vertical integration or other factors?... More