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      Evidence for Citation Networks in Studies of Free-Roaming Cats: A Case Study Using Literature on Trap–Neuter–Return (TNR)

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      Animals : an Open Access Journal from MDPI
      MDPI
      TNR, citation bias, citation network

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          Abstract

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          All aspects of an argument need to be evaluated in evidence-based scientific pursuit to prevent the development of self-reinforcing cohorts of studies through the cross-referencing of selected subsets of studies (citation bias). Controling populations of unowned cats using Trap–Neuter–Return and its variants (hereafter TNR) is an example of how a scientific topic develops and is communicated academically and publicly. We found 145 TNR publications between 2002–2019, with the last two years seeing a rapid increase in studies. Publication clusters occur, focusing on: population control, interactions with wildlife, disease transmission (including implications for pet cats, wildlife and humans), free-roaming cats, and feral and domestic cat management. A quarter of all studies were published in Open Access formats, which have the highest potential social impact because they are free to download, share and read. While it is encouraging that diverse views are expressed, the development of clusters of introspective topics risks reduced dialogue between groups of authors with differing views. Journal editors could encourage exchanges between groups by choosing reviewers from different camps to assess manuscripts and by asking authors to acknowledge alternative views.

          Abstract

          Trap–Neuter–Return and its variants (hereafter TNR) aims to control unowned cat populations. Papers on this topic form a useful case study of how how an area of literature grows, papers become influential, and citation networks form, influencing future study as well as public perceptions of the science. We analysed 145 TNR studies published 2002–2019. Common topics, identified by frequently used language, were population control, interactions with wildlife, disease transmission (including implications for pets, wildlife and humans), free-roaming cats, and feral and domestic cat management. One or more papers on each of these topics was judged influential because of high citations overall, high average citations/year, or frequent mentions in social media. Open Access papers were more influential in social media, raising greater public awareness than studies published in journals that were less accessible. While divergent views exist on a range of topics, the network analysis of the TNR literature indicated potential for forming self-reinforcing groups of authors. While it is encouraging that diverse views are expressed, there is a risk of reduced dialogue interactions between groups, potentially constraining dialogue to refine arguments, share information, or plan research. Journal editors could encourage communication by choosing reviewers from different camps to assess manuscripts and by asking authors to acknowledge alternative views.

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          Citation-based clustering of publications using CitNetExplorer and VOSviewer

          Clustering scientific publications in an important problem in bibliometric research. We demonstrate how two software tools, CitNetExplorer and VOSviewer, can be used to cluster publications and to analyze the resulting clustering solutions. CitNetExplorer is used to cluster a large set of publications in the field of astronomy and astrophysics. The publications are clustered based on direct citation relations. CitNetExplorer and VOSviewer are used together to analyze the resulting clustering solutions. Both tools use visualizations to support the analysis of the clustering solutions, with CitNetExplorer focusing on the analysis at the level of individual publications and VOSviewer focusing on the analysis at an aggregate level. The demonstration provided in this paper shows how a clustering of publications can be created and analyzed using freely available software tools. Using the approach presented in this paper, bibliometricians are able to carry out sophisticated cluster analyses without the need to have a deep knowledge of clustering techniques and without requiring advanced computer skills.
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            Why people fail to recognize their own incompetence

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              Google Scholar as a new source for citation analysis

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                Author and article information

                Journal
                Animals (Basel)
                Animals (Basel)
                animals
                Animals : an Open Access Journal from MDPI
                MDPI
                2076-2615
                06 June 2020
                June 2020
                : 10
                : 6
                : 993
                Affiliations
                Environmental and Conservation Sciences, Murdoch University, Murdoch WA 6150, Australia; T.Fleming@ 123456murdoch.edu.au
                Author notes
                [* ]Correspondence: m.calver@ 123456murdoch.edu.au ; Tel.: +61-8-9360-2277
                Author information
                https://orcid.org/0000-0002-0626-3851
                Article
                animals-10-00993
                10.3390/ani10060993
                7341228
                32517234
                5035b8d7-8c98-4541-947e-8fc38636a0eb
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 05 May 2020
                : 28 May 2020
                Categories
                Article

                tnr,citation bias,citation network
                tnr, citation bias, citation network

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