What Does What We Read Tell Us About Ourselves? Analyzing TCR's Network of Papers and Readers
by Brian V. Carolan — November 15, 2006
Recent criticism about the field of educational research suggests that efforts to develop greater consensus are inhibited by the field’s lack of connectivity.
Purpose/Objective/Research Question/Focus of Study:
The objective of this study is to examine the extent to which the educational field is connected and infer what these connections mean for developing greater cohesion across the field’s topical boundaries.
A one-mode interlock network of papers was derived from a bipartite graph of readers and papers drawn from the Teachers College Record’s (TCR) online database. Information on 70,000 unique readers and 2400 papers between the years 2000–2003 was ultimately projected into a one-mode graph consisting of 255 papers. Ties between each pair of papers were established using the percentage of audience overlap. Only papers with a minimum of 400 unique readers were included in the analysis.
Using this one-mode of relations between papers, several social network algorithms were applied to test three competing structural models: small-world, scale-free, and structurally cohesive.
Though data limitations demand cautious interpretation, the network reveals a clear small-world pattern which indicates that papers are highly clustered, yet the average distance between any pair is relatively short when compared to a properly adjusted random graph with a similar degree distribution. Moreover, further analyses reveal a multivocal hub community of papers that are disproportionately responsible for connecting disparate clusters.
The small-world model revealed in these data suggests an imagery of educational research in which topical clustering co-exists with an encouraging amount of topical mixing. This mixing space is considered to be the key mechanism through which greater consensus can be promoted.
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