  In this paper, we analyze the adequacy and applicability of readership
statistics recorded in social reference management systems for creating
knowledge domain visualizations. First, we investigate the distribution of
subject areas in user libraries of educational technology researchers on
Mendeley. The results show that around 69% of the publications in an average
user library can be attributed to a single subject area. Then, we use
co-readership patterns to map the field of educational technology. The
resulting visualization prototype, based on the most read publications in this
field on Mendeley, reveals 13 topic areas of educational technology research.
The visualization is a recent representation of the field: 80% of the
publications included were published within ten years of data collection. The
characteristics of the readers, however, introduce certain biases to the
visualization. Knowledge domain visualizations based on readership statistics
are therefore multifaceted and timely, but it is important that the
characteristics of the underlying sample are made transparent.
