• Admin Login
    View Item 
    •   Home
    • Theses and Dissertations
    • Theses and Dissertations
    • View Item
    •   Home
    • Theses and Dissertations
    • Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of WIRECommunitiesTitleAuthorsIssue DateSubmit DateSubjectsTypesJournalDepartmentPublisherThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsTypesJournalDepartmentPublisher

    Administrators

    Admin Login

    Local Links

    AboutThe University LibraryOpen Access Publications PolicyDeposit LicenceCOREWIRE Copyright and Reuse Information

    Statistics

    Display statistics

    Identifying the Invisible Impact of Scholarly Publications: A Multi-Disciplinary Analysis Using Altmetrics

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    MohammadiPhD Thesis.pdf
    Size:
    2.253Mb
    Format:
    PDF
    Download
    Authors
    Mohammadi, Ehsan
    Issue Date
    2018
    
    Metadata
    Show full item record
    Abstract
    The field of ‘altmetrics’ is concerned with alternative metrics for the impact of research publications using social web data. Empirical studies are needed, however, to assess the validity of altmetrics from different perspectives. This thesis partly fills this gap by exploring the suitability and reliability of two altmetrics resources: Mendeley, a social reference manager website, and Faculty of F1000 (F1000), a post- publishing peer review platform. This thesis explores the correlations between the new metrics and citations at the level of articles for several disciplines and investigates the contexts in which the new metrics can be useful for research evaluation across different fields. Low and medium correlations were found between Mendeley readership counts and citations for Social Sciences, Humanities, Medicine, Physics, Chemistry and Engineering articles from the Web of Science (WoS), suggesting that Mendeley data may reflect different aspects of research impact. A comparison between information flows based on Mendeley bookmarking data and cross-disciplinary citation analysis for social sciences and humanities disciplines revealed substantial similarities and some differences. This suggests that Mendeley readership data could be used to help identify knowledge transfer between scientific disciplines, especially for people that read but do not author articles, as well as providing evidence of impact at an earlier stage than is possible with citation counts. The majority of Mendeley readers for Clinical Medicine, Engineering and Technology, Social Science, Physics and Chemistry papers were PhD students and postdocs. The highest correlations between citations and Mendeley readership counts were for types of Mendeley users that often authored academic papers, suggesting that academics bookmark papers in Mendeley for reasons related to scientific publishing. In order to identify the extent to which Mendeley bookmarking counts reflect readership and to establish the motivations for bookmarking scientific papers in Mendeley, a large-scale survey found that 83% of Mendeley users read more than half of the papers in their personal libraries. The main reasons for bookmarking papers were citing in future publications, using in professional activities, citing in a thesis, and using in teaching and assignments. Thus, Mendeley bookmarking counts can potentially indicate the readership impact of research papers that have educational value for non-author users inside academia or the impact of research papers on practice for readers outside academia. This thesis also examines the relationship between article types (i.e., “New Finding”, “Confirmation”, “Clinical Trial”, “Technical Advance”, “Changes to Clinical Practice”, “Review”, “Refutation”, “Novel Drug Target”), citation counts and F1000 article factors (FFa). In seven out of nine cases, there were no significant differences between article types in terms of rankings based on citation counts and the F1000 Article Factor (FFa) scores. Nevertheless, citation counts and FFa scores were significantly different for articles tagged: “New finding” or “Changes to Clinical Practice”. This means that F1000 could be used in research evaluation exercises when the importance of practical findings needs to be recognised. Furthermore, since the majority of the studied articles were reviewed in their year of publication, F1000 could also be useful for quick evaluations.
    URI
    http://hdl.handle.net/2436/621986
    Type
    Thesis or dissertation
    Language
    en
    Description
    A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.
    Collections
    Theses and Dissertations

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.