8
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Real-Time Bibliometrics: Dimensions as a Resource for Analyzing Aspects of COVID-19

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Dimensions was built as a platform to allow stakeholders in the research community, including academic bibliometricians, to more easily create and understand the context of different types of research object through the linkages between these objects. Links between objects are created via persistent identifiers and machine learning techniques, while additional context is introduced via data enhancements such as per-object categorisations and person and institution disambiguation. While these features make analytical use cases accessible for end users, the COVID-19 crisis has highlighted a different set of needs to analyze trends in scholarship as they occur: Real-time bibliometrics. The combination of full-text search, daily data updates, a broad set of scholarly objects including pre-prints and a wider set of data fields for analysis, broadens opportunities for a different style of analysis. A subset of these emerging capabilities is discussed and three basic analyses are presented as illustrations of the potential for real-time bibliometrics.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software

          Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics…). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users’ typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Are women publishing less during the pandemic? Here’s what the data say

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              The pandemic and the female academic

                Bookmark

                Author and article information

                Contributors
                Journal
                Front Res Metr Anal
                Front Res Metr Anal
                Front. Res. Metr. Anal.
                Frontiers in Research Metrics and Analytics
                Frontiers Media S.A.
                2504-0537
                12 January 2021
                2020
                12 January 2021
                : 5
                : 595299
                Affiliations
                [ 1 ]Digital Science, London, United Kingdom
                [ 2 ]Centre for Complexity Science, Imperial College London, London, United Kingdom
                [ 3 ]Department of Physics, Washington University in St Louis, St Louis, MO, United States
                Author notes
                *Correspondence: Daniel W. Hook, daniel@ 123456digital-science.com

                This article was submitted to Scholarly Communication, a section of the journal Frontiers in Research Metrics and Analytics

                Edited by: Dietmar Wolfram, University of Wisconsin–Milwaukee, United States

                Reviewed by: Yi Zhang, University of Technology Sydney, Australia

                Ricardo Arencibia-Jorge, Universidad Nacional Autónoma de México, Mexico

                Article
                595299
                10.3389/frma.2020.595299
                8104272
                33969256
                752da27b-bd58-4dbf-8671-afb8d6ad4745
                Copyright © 2021 Hook, Porter, Draux and Herzog

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 August 2020
                : 25 November 2020
                Categories
                Original Research
                Original Research

                timescale,peer review,collaboration,gender,dimensions,covid-19 crisis,full text search,real-time bibliometrics

                Comments

                Comment on this article