Hypothesis - Bartle types as network agents

About a year ago I took the time to read through this http://www.tp.umu.se/~rosvall/publications/rosvall-phd.pdf which contains some interesting perspectives about the world which I find relevant to game design. The first quite practical idea that struck me from thinking along the lines presented is that we can look at the commonly used four Bartle types as agents in an information network. Before I go straight at the idea I have to describe what I mean by information network in relationship to this particular post.

An information network is any system which relays information through links to nodes. For the case of a an online game, which is where the Bartle types come from, this information is typically in the form of text, number, items, levels and so on. We can summarize it as everything any player does which can be observed by any other player either directly or indirectly as a piece of information in the network. The nice thing is that we don’t have to care about the details here.

If you want a good background for understanding the following arguments I recommend reading the publication linked at the beginning of this post. Otherwise maybe you might be interested in it for some other reason.

Quick and dirty Information Network theory background

Nodes are positions and actors in the system, for the case of this particular perspective they are players.

Links are connections between players which transfer information. A Chat conversation is a link, group membership, trade, spatial proximity and so on. We can categorize links as a kind of relationship between players. Links are commonly measured as a relative strength. Measuring links in a binary fashion as used in this text implicates that there is some threshold under which the relationship is too weak to warrant representation in the model. For example between two players who briefly saw each other or had a brief conversation. If you have a project where this type of detail is of relevance feel welcome to extend the model to fit the data which you can understand.

An important piece of background for understanding this text is that links are attracted to nodes which has and communicates information.

Some poorly formulated theory follows:

Bartle types can be detected within a game by tracking changes to the information network. How you would do this practically is not going to be part of this post. Each player can be considered as a node, or we can group players together if you like, but on this very abstract level it does not matter, at least not to me.

The Achiever is a node which generate information through its activities. The Achiever activities are typically focused on explicit goals within the system, such as obtaining things of value. The information gathered by the Achiever is primarily about the Achiever as a relationship to these goals. Such information will spread out from its source to other nodes in the system.

The Explorer determines the value and priority of information in the network. The values found by the Explorer are relevant as meta information and attract links just as any information does. By careful examination and comparisons of available information the explorer is the node which labels information as more or less relevant within the system. If you have played some WoW you might argue that this is done by the auction house, I would argue that there are other things which are information, such as raid tactics, rare spawns, cute little pets, fun quests, interesting situations, chat conventions and about everything else.

The Socializer is a node which relays information by attaching links to available nodes. Information and the priority of information attract attention from the Socializer. Once the Socializer node has obtained information it will use the information to attract new links.

The Killer is a node which cut the network by removing links and nodes. The Killer is unpredictable and will at random select a piece of the network and cut it. We can make a guess which says that the Killer will cut the network at about 2 degrees separation, or more, from its own position.