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Benjakob O, Guley O, Sevin JM, Blondel L, Augustoni A, Collet M, Jouveshomme L, Amit R, Linder A, Aviram R. Wikipedia as a tool for contemporary history of science: A case study on CRISPR. PLoS One 2023; 18:e0290827. [PMID: 37703244 PMCID: PMC10499201 DOI: 10.1371/journal.pone.0290827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 08/16/2023] [Indexed: 09/15/2023] Open
Abstract
Rapid developments and methodological divides hinder the study of how scientific knowledge accumulates, consolidates and transfers to the public sphere. Our work proposes using Wikipedia, the online encyclopedia, as a historiographical source for contemporary science. We chose the high-profile field of gene editing as our test case, performing a historical analysis of the English-language Wikipedia articles on CRISPR. Using a mixed-method approach, we qualitatively and quantitatively analyzed the CRISPR article's text, sections and references, alongside 50 affiliated articles. These, we found, documented the CRISPR field's maturation from a fundamental scientific discovery to a biotechnological revolution with vast social and cultural implications. We developed automated tools to support such research and demonstrated its applicability to two other scientific fields-coronavirus and circadian clocks. Our method utilizes Wikipedia as a digital and free archive, showing it can document the incremental growth of knowledge and the manner scientific research accumulates and translates into public discourse. Using Wikipedia in this manner compliments and overcomes some issues with contemporary histories and can also augment existing bibliometric research.
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Affiliation(s)
- Omer Benjakob
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Olha Guley
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Jean-Marc Sevin
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Leo Blondel
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Ariane Augustoni
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Matthieu Collet
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Louise Jouveshomme
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Roy Amit
- Bezalel Academy of Arts and Design, Jerusalem, Israel
| | - Ariel Linder
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
| | - Rona Aviram
- System Engineering and Evolution Dynamics, Inserm, Université Paris Cité, Paris, France
- Learning Planet Institute, Paris, France
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Schmidt M, Kircheis W, Simons A, Potthast M, Stein B. A diachronic perspective on citation latency in Wikipedia articles on CRISPR/Cas-9: an exploratory case study. Scientometrics 2023; 128:3649-3673. [PMID: 37228830 PMCID: PMC10183088 DOI: 10.1007/s11192-023-04703-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 03/28/2023] [Indexed: 05/27/2023]
Abstract
This paper analyzes Wikipedia's representation of the Nobel Prize winning CRISPR/Cas9 technology, a method for gene editing. We propose and evaluate different heuristics to match publications from several publication corpora against Wikipedia's central article on CRISPR and against the complete Wikipedia revision history in order to retrieve further Wikipedia articles relevant to the topic and to analyze Wikipedia's referencing patterns. We explore to what extent the selection of referenced literature of Wikipedia's central article on CRISPR adheres to scientific standards and inner-scientific perspectives by assessing its overlap with (1) the Web of Science (WoS) database, (2) a WoS-based field-delineated corpus, (3) highly-cited publications within this corpus, and (4) publications referenced by field-specific reviews. We develop a diachronic perspective on citation latency and compare the delays with which publications are cited in relevant Wikipedia articles to the citation dynamics of these publications over time. Our results confirm that a combination of verbatim searches by title, DOI, and PMID is sufficient and cannot be improved significantly by more elaborate search heuristics. We show that Wikipedia references a substantial amount of publications that are recognized by experts and highly cited, but that Wikipedia also cites less visible literature, and, to a certain degree, even not strictly scientific literature. Delays in occurrence on Wikipedia compared to the publication years show (most pronounced in case of the central CRISPR article) a dependence on the dynamics of both the field and the editor's reaction to it in terms of activity.
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Affiliation(s)
- Marion Schmidt
- German Center for Higher Education Research and Science Studies (DZHW), Berlin, Germany
| | - Wolfgang Kircheis
- Leipzig University and Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Leipzig, Germany
| | - Arno Simons
- Technische Universität Berlin, German Center for Higher Education Research and Science Studies (DZHW), Berlin, Germany
| | - Martin Potthast
- Leipzig University and Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Leipzig, Germany
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Whaley AL, Mesidor JK. Teaching publication ethics to clinical psychology doctoral students: case-based learning and semi-structured interview strategies. ETHICS & BEHAVIOR 2023. [DOI: 10.1080/10508422.2023.2169829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Affiliation(s)
| | - Jean Kesnold Mesidor
- Department of Behavioral Sciences and Social Medicine, Florida State University College of Medicine
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Zheng X, Chen J, Yan E, Ni C. Gender and country biases in Wikipedia citations to scholarly publications. J Assoc Inf Sci Technol 2022. [DOI: 10.1002/asi.24723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Xiang Zheng
- Information School University of Wisconsin‐Madison Madison Wisconsin USA
| | - Jiajing Chen
- Information School University of Wisconsin‐Madison Madison Wisconsin USA
- Department of Computer Science Courant Institute of Mathematical Sciences, New York University New York New York USA
| | - Erjia Yan
- College of Computing & Informatics Drexel University Philadelphia Pennsylvania USA
| | - Chaoqun Ni
- Information School University of Wisconsin‐Madison Madison Wisconsin USA
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Zagorova O, Ulloa R, Weller K, Flöck F. “I updated the <ref>”: The evolution of references in the English Wikipedia and the implications for altmetrics. QUANTITATIVE SCIENCE STUDIES 2021. [DOI: 10.1162/qss_a_00171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Abstract
With this work, we present a publicly available data set of the history of all the references (more than 55 million) ever used in the English Wikipedia until June 2019. We have applied a new method for identifying and monitoring references in Wikipedia, so that for each reference we can provide data about associated actions: creation, modifications, deletions, and reinsertions. The high accuracy of this method and the resulting data set was confirmed via a comprehensive crowdworker labeling campaign. We use the data set to study the temporal evolution of Wikipedia references as well as users’ editing behavior. We find evidence of a mostly productive and continuous effort to improve the quality of references: There is a persistent increase of reference and document identifiers (DOI, PubMedID, PMC, ISBN, ISSN, ArXiv ID) and most of the reference curation work is done by registered humans (not bots or anonymous editors). We conclude that the evolution of Wikipedia references, including the dynamics of the community processes that tend to them, should be leveraged in the design of relevance indexes for altmetrics, and our data set can be pivotal for such an effort.
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Affiliation(s)
- Olga Zagorova
- GESIS - Leibniz-Institut für Sozialwissenschaften in Koln, Germany
| | - Roberto Ulloa
- GESIS - Leibniz-Institut für Sozialwissenschaften in Koln, Germany
| | - Katrin Weller
- GESIS - Leibniz-Institut für Sozialwissenschaften in Koln, Germany
| | - Fabian Flöck
- GESIS - Leibniz-Institut für Sozialwissenschaften in Koln, Germany
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