It’s often useful to think about the visualisation design space before thinking about point designs. However, the visualisation design space is large. By scaffolding it, we can reassure ourselves that we haven’t missed an obvious point design.
In the previous post, we used term profiles to judge the effects of participation inequality in simulated collections of 100 photographs. In this post, we will use them to judge the effects of participation inequality in Geograph, a collection of nearly six million photographs of Great Britain and Ireland.
Let’s say you have a collection of photographs: each was taken by a user, who also added a tag and a location. Let’s say you’d like to understand some aspect of these photographs, such as which tags are associated with which locations. However, there’s a problem: a small number of users took a large number of photographs. To what extent will your understanding of the relationships between tags and locations be biased by how these users tagged these photographs?
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