Leveraging Citation Networks to Visualize Scholarly Influence Over Time

Portenoy, Jason; Hullman, Jessica; West, Jevin D.

doi:10.3389/frma.2017.00008

Cited by 37 publications

(11 citation statements)

References 41 publications

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“…The predecessor of MA, Microsoft Academic Search, was decommissioned towards the end of 2016 and attracted little bibliometric research. Harzing (2016) identified only six journal articles related to Microsoft Academic Search and bibliometrics. In contrast, MA has already spurred great interest in a short period of time and triggered several studies that focus on bibliometric topics, such as four studies on visualization and mapping (De Domenico, Omodei, & Arenas, 2016;Portenoy, Hullman, & West, 2016;Portenoy, & West, 2017, Tan et al, 2016. Furthermore, there are eleven studies that deal with the development of indicators and algorithms (Effendy & Yap, 2016;Effendy & Yap, 2017;Herrmannova & Knoth, 2016b;Luo, Gong, Hu, Duan, & Ma, 2016;Medo & Cimini, 2016;Ribas, Ueda, Santos, Ribeiro-Neto, & Ziviani, 2016;Sandulescu & Chiru, 2016;Wesley-Smith, Bergstrom, & West, 2016;Vaccario, Medo, Wider, & Mariani, 2017;Wilson, Mohan, Arif, Chaudhury, & Lall, 2016;Xiao et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

The coverage of Microsoft Academic: analyzing the publication output of a university

Hug

Brändle

2017

Scientometrics

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This is the first detailed study on the coverage of Microsoft Academic (MA). Based on the complete and verified publication list of a university, the coverage of MA was assessed and compared with two benchmark databases, Scopus and Web of Science (WoS), on the level of individual publications. Citation counts were analyzed, and issues related to data retrieval and data quality were examined. A Perl script was written to retrieve metadata from MA based on publication titles. The script is freely available on GitHub. We find that MA covers journal articles, working papers, and conference items to a substantial extent and indexes more document types than the benchmark databases (e.g., working papers, dissertations). MA clearly surpasses Scopus and WoS in covering book-related document types and conference items but falls slightly behind Scopus in journal articles. The coverage of MA is favorable for evaluative bibliometrics in most research fields, including economics/business, computer/information sciences, and mathematics. However, MA shows biases similar to Scopus and WoS with regard to the coverage of the humanities, non-English publications, and open-access publications. Rank correlations of citation counts are high between MA and the benchmark databases. We find that the publication year is correct for 89.5% of all publications and the number of authors is correct for 95.1% of the journal articles. Given the fast and ongoing development of MA, we conclude that MA is on the verge of becoming a bibliometric superpower. However, comprehensive studies on the quality of MA metadata are still lacking.

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Section: Introductionmentioning

confidence: 99%

The coverage of Microsoft Academic: analyzing the publication output of a university

Hug

Brändle

2017

Scientometrics

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“…To visualize the relationship between texts cited by different guidance, quantitative citation networks (Portenoy et al., 2017) were developed by converting reference data into network objects using the R Studio v3.5.2 network package (Butts et al., 2019). Networks, in which texts and citations were represented as nodes and edges, respectively, were then plotted via the ‘ggnet2’ function of the R Studio v3.5.2 GGally package (Schloerke et al., 2020), using a Fruchterman–Reingold algorithm.…”

Section: Methodsmentioning

confidence: 99%

Evidence shortfalls in the recommendations and guidance underpinning ecological mitigation for infrastructure developments

Hunter

Ermgassen

Downey

et al. 2021

Ecol Sol and Evidence

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1. In the United Kingdom and European Union, legal protection of species from the impacts of infrastructure development depends upon a number of ecological mitigation and compensation (EMC) measures to moderate the conflict between development and conservation. However, the scientific evidence supporting their effectiveness has not yet been comprehensively assessed.2. This study compiled the measures used in practice, identified and explored the guidance that informed them and, using the Conservation Evidence database, evaluated the empirical evidence for their effectiveness.3. In a sample of 50 U.K. housing applications, we identified the recommendation of 446 measures in total, comprising 65 different mitigation measures relating to eight taxa. Although most (56%) measures were justified by citing published guidance, exploration of the literature underpinning this guidance revealed that empirical evaluations of EMC measure effectiveness accounted for less than 10% of referenced texts. Citation network analysis also identified circular referencing across bat, amphibian and reptile EMC guidance. Comparison with Conservation Evidence synopses showed that over half of measures recommended in ecological reports had not been empirically evaluated, with only 13 measures assessed as beneficial.4. As such, most EMC measures recommended in practice are not evidence based.The limited reference to empirical evidence in published guidance, as well as the circular referencing, suggests potential 'evidence complacency' , in which evidence is not sought to inform recommendations. In addition, limited evidence availability indicates a thematic gap between conservation research and mitigation practice.More broadly, absence of evidence on the effectiveness of EMC measures calls into question the ability of current practice to compensate for the impact of development on protected species, thus highlighting the need to strengthen requirements for impact avoidance. Given the recent political drive to invest in infrastructureThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…One promising implementation, built with data from MA is the Author Level Eigenfactor, or ALEF (Wesley-Smith, Bergstrom, and West 2016). Particularly intriguing is their suggestion in a subsequent paper (Portenoy, Hullman, and West 2016) to graph authors' influence networks, which depict a multi-dimensional picture rather than a single score. The authors provide a website (scholar.eigenfactor.org) allowing users to generate such graphs.…”

Section: Flexibilitymentioning

confidence: 99%

Impact Metrics

Gerring¹,

Karcher²,

Apfeld³

2021

Preprint

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In recent decades, another metric has come to the fore that takes a fundamentally different approach to evaluation. This approach measures impact, inferred from the citations accrued by a study. Like reputation, impact may be measured at any level. An individual may be evaluated according to the citations accruing to her publications; a department may be evaluated according to the citations accrued by studies produced by all its faculty; a journal or press may be evaluated according to the citations accrued by all its publications; and so forth. Naturally, there is some inter-dependence among impact measures. A study’s citation-count is apt to be influenced by a journal’s citation-count, for example. Nonetheless, there is a much greater degree of independence among the units being assessed. An implication is that impact-based metrics are more meritocratic than reputational metrics

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Leveraging Citation Networks to Visualize Scholarly Influence Over Time

Cited by 37 publications

References 41 publications

The coverage of Microsoft Academic: analyzing the publication output of a university

The coverage of Microsoft Academic: analyzing the publication output of a university

Evidence shortfalls in the recommendations and guidance underpinning ecological mitigation for infrastructure developments

Impact Metrics

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