A paper in the British Medical Journal by Steven Greenberg examines the use of citations around a meme in the medical literature. The meme was that beta-amyloid protein "is produced by and injures skeletal muscle of patients with inclusion body myositis". Apparently this is false, but a huge number of papers state that it is true. From the abstract:
"Design A complete citation network was constructed from all PubMed indexed English literature papers addressing the belief that β 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.
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."
I've seen a lot of these things going on in economics, including the misrepresentation of my own work on the environmental Kuznets curve meme :) I'm probably guilty of some these practices myself too. And then there is a comment I wrote on someone's paper that I submitted to a journal but that was never published. I thought it would be published and so cited it in one of my papers. The comment has been cited by three people so far according to Google Scholar though the only place the paper actually exists is on my computer.
HT: Peter Martin
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