bq. Design: A complete citation network was constructed from all PubMed indexed English literature papers addressing the belief that ? amyloid, a protein accumulated in the brain in Alzheimer’s disease, is produced by and injures skeletal muscle of patients with inclusion body myositis. Social network theory and graph theory were used to analyse this network.
bq. Results: The network contained 242 papers and 675 citations addressing the belief, with 220 553 citation paths supporting it. Unfounded authority was established by citation bias against papers that refuted or weakened the belief; amplification, the marked expansion of the belief system by papers presenting no data addressing it; and forms of invention such as the conversion of hypothesis into fact through citation alone. Extension of this network into text within grants funded by the National Institutes of Health and obtained through the Freedom of Information Act showed the same phenomena present and sometimes used to justify requests for funding.
bq. Conclusion: Citation is both an impartial scholarly method and a powerful form of social communication. Through distortions in its social use that include bias, amplification, and invention, citation can be used to generate information cascades resulting in unfounded authority of claims. Construction and analysis of a claim specific citation network may clarify the nature of a published belief system and expose distorted methods of social citation.
From a fascinating piece by Steven Greenberg in the BMJ. I am often struck by how citation patterns — not just exclusion or inclusion, but misrepresentation of arguments, or what Greenberg calls “citation diversion” — develop within the literatures that I work in. For example, on a recent graduate student comprehensive exam, this student argued that Philip Converse believes that American voters are “stupid.”
We should probably train academics to read through literatures and synthesize them accurately, but few want to take the time. We focus on producing new original research and not on describing the extant research correctly. In fact, the misrepresentations of previous work often serve our own purposes: to make our work look more counterintuitive, path-breaking, or whatever. I am undoubtedly guilty of this.
When I first read the earliest studies of American presidential campaigns, I remarked to a colleague how well these books covered the field, and how much subsequent literature has been simply refinement.
My colleague was more pessimistic: “We’ve been un-learning what they learned,” he said.
Citation bias, and the resulting inefficiencies and distortions in the accumulation of knowledge, seem one reason for this.
[Hat tip to Julie Lynch.]