Affiliation:
1. School of Information Sciences, The University of Tennessee, Knoxville, USA
2. Center for Knowledge Management, Vanderbilt University Medical Center, USA
Abstract
Faculty Opinions has provided recommendations of important biomedical publications by domain experts (FMs) since 2001. The purpose of this study is two-fold: (1) identify the characteristics of the expert-recommended articles that were subsequently retracted and (2) investigate what happened after retraction. We examined a set of 232 recommended, later retracted or corrected articles. These articles were classified as New Finding (43%), Interesting Hypothesis (16%), and so on. More than 71% of the articles acknowledged funding support; the National Institutes of Health, USA (NIH) was a top funder (64%). The top reasons for retractions were Errors of various types (28%); Falsification/fabrication of data, image, or results (20%); Unreliable data, image, or results (16%); and Results not reproducible (16%). Retractions took from less than 2 months to more than 15 years. Only 15% of recommendations were withdrawn either after dissents were made by other FMs or after retractions. Most of the retracted articles continue to be cited post-retraction, especially those published in Nature, Science, and Cell. Significant positive correlations were observed between post-retraction citations and pre-retraction citations, between post-retraction citations and peak citations, and between post-retraction citations and the post-retraction citing span. A significant negative correlation was also observed between the post-retraction citing span and years taken to reach peak citations. Literature recommendation systems need to update the changing status of the recommended articles in a timely manner; invite the recommending experts to update their recommendations; and provide a personalised mechanism to alert users who have accessed the recommended articles on their subsequent retractions, concerns, or corrections.
Subject
Library and Information Sciences,Information Systems
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