A protocol to gather, characterize and analyze incoming citations of retracted articles

Ivan Heibi and Silvio Peroni

PLOS ONE, 2022, vol. 17, issue 7, 1-24

Abstract: In this article, we present a methodology which takes as input a collection of retracted articles, gathers the entities citing them, characterizes such entities according to multiple dimensions (disciplines, year of publication, sentiment, etc.), and applies a quantitative and qualitative analysis on the collected values. The methodology is composed of four phases: (1) identifying, retrieving, and extracting basic metadata of the entities which have cited a retracted article, (2) extracting and labeling additional features based on the textual content of the citing entities, (3) building a descriptive statistical summary based on the collected data, and finally (4) running a topic modeling analysis. The goal of the methodology is to generate data and visualizations that help understanding possible behaviors related to retraction cases. We present the methodology in a structured step-by-step form following its four phases, discuss its limits and possible workarounds, and list the planned future improvements.

Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0270872

DOI: 10.1371/journal.pone.0270872

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