Wikiometrics: a Wikipedia based ranking system

Katz, Gilad; Rokach, Lior

doi:10.1007/s11280-016-0427-8

Cited by 12 publications

(9 citation statements)

References 37 publications

(23 reference statements)

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“…In addition WRWU2013 attracted a significant interest world wide (see [21] and various press highlights listed at [22]). Other research groups also start to apply Wikipedia ranking in Wikiometrics [23]. We also note the growing interest to scientific analysis of several language editions of Wikipedia [24].…”

Section: Introductionmentioning

confidence: 99%

World influence and interactions of universities from Wikipedia networks

2019

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We present Wikipedia Ranking of World Universities (WRWU) based on analysis of networks of 24 Wikipedia editions collected in May 2017. With PageRank and CheiRank algorithms we determine ranking of universities averaged over cultural views of these editions. The comparison with the Shanghai ranking gives overlap of 60% for top 100 universities showing that WRWU gives more significance to their historical development. We show that the new reduced Google matrix algorithm allows to determine interactions between leading universities on a scale of ten centuries. This approach also determines the influence of specific universities on world countries. We also compare different cultural views of Wikipedia editions on significance and influence of universities. PACS. 89.75.Fb Structures and organization in complex systems -89.75.Hc Networks and genealogical trees -89.20.Hh World Wide Web, Internet Paris-Sorbonne Pantheon-Sorbonne EPHE ENS Polytechnique USC UW-Madison Florida UT Austin NYU UPenn UCLA Cornell Michigan Chicago Princeton Berkeley MIT Stanford Yale Columbia HarvardHarvard Columbia Yale Stanford MIT Berkeley Princeton Chicago Michigan Cornell UCLA UPenn NYU UT Austin Florida UW-Madison USC Polytechnique ENS EPHE Paris-Sorbonne Pantheon-Sorbonne EPHE ENS Polytechnique USC UW-Madison Florida UT Austin NYU UPenn UCLA Cornell Paris-Sorbonne Pantheon-Sorbonne EPHE ENS Polytechnique USC UW-Madison Florida UT Austin NYU UPenn UCLA Cornell Harvard Columbia Yale Stanford MIT Berkeley Princeton Chicago Michigan Cornell UCLA UPenn NYU UT Austin Florida UW-Madison USC Polytechnique ENS EPHE

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Section: Introductionmentioning

confidence: 99%

World influence and interactions of universities from Wikipedia networks

2019

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“…It is challenging to demonstrate career productivity with Wikipedia as a platform, 13 though benchmarks could address this limitation. 17 Intrinsic biases against Wikipedia must also be addressed. Indeed age, gender, political and comfortability with technology have been shown to create significant biases within editing and usage of Wikipedia.…”

Section: Discussionmentioning

confidence: 99%

Wikipedia: A Medical Student Educational Project to Edit Wikipedia in Preparation for Practicing Evidence-Based Pain Medicine

Kantarovich

Vollbrecht

Cruz

et al. 2020

Journal of Medical Education and Curricular Development

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Objective: Wikipedia is commonly used to acquire information about various medical conditions such as chronic pain. Ideally, better online pain management content could reduce the burden of opioid use disorders. Our goal was to improve the quality of the content available on Wikipedia to make it more accurate and applicable to medical students and the general public while training medical students to practice evidence-based medicine and critically assess their sources of information. Methods: An elective class in Neuroscience, Pain, and Opioids composed of 10 medical students met biweekly to discuss landmark and practice-changing research articles in the fields of acute pain, chronic pain, and opioid management. The professor chose Wikipedia articles relevant to this course. Three independent viewers analyzed the quality of citations, anecdotal medical content, and content value for both patients and medical professionals. As part of their coursework, students then edited the Wikipedia articles. Results: Although some of the Wikipedia pain topic content (6.7% ± 2.0) was anecdotal, financially biased, or inconsistent with Western Medical Practice content, overall articles included primarily high-quality citations (85.6% ± 3.1). On a 0-5 Likert scale, students felt content would be moderately helpful for both medical students/professionals (3.4 ± 0.2) and laypersons (3.5 ± 0.2). Editing and adding citations was feasible, but novel material was often reverted. Conclusion: A significant amount of pain medicine content was relevant and amenable to student editing. Therefore, future use of this tactic could provide a unique opportunity to integrate evidence-based medicine into the medical curriculum and have a direct impact on the widely available medical information. Future refinement in the editorial process may also further improve online information.

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“…New communication technologies have enabled research on the impact of scientific research beyond traditional scholarly journals. Blog posts, tweets, articles and links from Wikipedia, citations from books—all this digital content became a rich source of data for various bibliometric studies [8], [9], [10], [11], [12], [13], [14]. This has encouraged the creation of new indicators, metrics, and tools for different aspects of scholarly communication and research output [13], [15], [16], [17], [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Comparing the topological rank of journals in Web of Science and Mendeley

Katchanov

Markova

Shmatko

2019

Heliyon

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Recently, there has been a surge of interest in new data emerged due to the rapid development of the information technologies in scholarly communication. Since the 2010s, altmetrics has become a common trend in scientometric research. However, researchers have not treated in much detail the question of the probability distributions underlying these new data. The principal objective of this study was to investigate one of the classic problems of scientometrics—the problem of citation and readership distributions. The study is based on the data obtained from two information systems: Web of Science and Mendeley. Here we based on the concept of the cumulative empirical distribution function to explore the differences and similarities between citations and readership counts of biological journals indexed in Web of Science and Mendeley. The basic idea was to determine, for any journal, a “size” (it is said to be the topological rank) of citation and readership empirical cumulative distributions, and then to compare distributions of the topological ranks of Web of Science and Mendeley. In order to verify our model, we employ it to the bibliometric and altmetric research of 305 biological journals indexed in Journal Citation Reports 2015. The findings show that both distributions of the topological rank of biological journals are statistically close to the Wakeby distribution. The findings presented in this study add to our understanding of information processes of the scholarly communication in the new digital environment.

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Wikiometrics: a Wikipedia based ranking system

Cited by 12 publications

References 37 publications

World influence and interactions of universities from Wikipedia networks

World influence and interactions of universities from Wikipedia networks

Wikipedia: A Medical Student Educational Project to Edit Wikipedia in Preparation for Practicing Evidence-Based Pain Medicine

Comparing the topological rank of journals in Web of Science and Mendeley

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