"Server Sample: RP (High), PvE (Medium), PvE (High), PvP (High), PvP (High) Sampling Period: 8/01/2005 12:00 am - 8/30/2005 12:00 am Sampling Resolution: ~12 minutes Parsing Method: The sample unit is each unique character. Each character was tracked across the server logs. wow eu Total playing time, lowest observed level, highest observed level, guild affiliation, and zones seen in were parsed. Data Filter: None Sample Size: 241,378 characters We've been working on social network data at the guild level and would like to give an overview of our approach before getting into the gory details of what we've found. As many of you already know, there are only a few variables that we are able to get at from the client-side, so actual character interaction is something we must approximate via proxy metrics. We'd like to describe the metrics that we have used, but please do not hesitate to suggest others that would be possible with the set of variables the client-side currently has access to. Guild Roster: Over the sampling period, we generated a list of all guilds we observed. wow euro Then we generated a roster for every guild consisting of every character who has been observed to have that guild tag. Co-Presence Metric: In each snapshot, find all members of each guild that are online. For each observed pair, increment the connection weight between these two characters by 1. In other words, this metric tabulates overall guild co-presence - the frequency at which members of a guild are online at the same time. Co-Location Metric: In each snapshot, find all members of each guild that are online and in the same zone (and only if the zone is not a main city zone). wow power leveling For each observed pair, increment the connection weight between these two characters by 1. In other words, this metric serves as a proxy for collaboration - the frequency at which members are working together at the same time. We've found that the co-location metric provides more readable and comprehensible graphs and have used this metric for most of our analyses.
Below, we present some social networks of guilds constructed using the co-location metric. wow powerleveling We have removed the names of characters but left in their class and level information. In the following social network graphs, connection weights are based on the co-location metric (with a minor threshold applied to exclude very weak ties). The weight of each line implies the collaboration frequency over the sampling period. Each node is marked by the character's class and level progression over the sampling period. wow power level The more connections a node has, the more central it is placed in the graph itself. Characters who were never co-located with others during the sampling period are depicted as free-floating nodes. All 4 guilds depicted had between 40-50 members. Therefore, the connection weights themselves are directly comparable between the guilds. Get more here:http://blogs.parc.com/playon/archives/2005/10/mapping_social.html" .
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