BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    •   Bradford Scholars
    • Engineering and Informatics
    • Engineering and Informatics Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Display statistics

    Ontology for cultural variations in interpersonal communication: building on theoretical models and crowdsourced knowledge

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    View/Open
    Thakker_et_al_JASIST.pdf (1.888Mb)
    Download
    Publication date
    2016
    Author
    Thakker, Dhaval
    Karanasios, S
    Blanchard, E.
    Lau, L.
    Dimitrova, V.
    Keyword
    Ontology; Knowledge engineering; Culture; Crowdsourced knowledge; Semantic tagging
    Rights
    © 2016 Wiley. This is the peer reviewed version of the following article: Thakker D, Karanasios S, Blanchard E et al (2016) Ontology for cultural variations in interpersonal communication: building on theoretical models and crowdsourced knowledge. Journal of the Association for Information Science and Technology, which has been published in final form at http://dx.doi.org/ 10.1002/asi.23824. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    The domain of cultural variations in interpersonal communication is becoming increasingly important in various areas, including human-human interaction (e.g. business settings) and humancomputer interaction (e.g. during simulations, or with social robots). User generated content (UGC) in social media can provide an invaluable source of culturally diverse viewpoints for supporting the understanding of cultural variations. However, discovering and organizing UGC is notoriously challenging and laborious for humans, especially in ill-defined domains such as culture. This calls for computational approaches to automate the UGC sensemaking process by using tagging, linking and exploring. Semantic technologies allow automated structuring and qualitative analysis of UGC, but are dependent on the availability of an ontology representing the main concepts in a specific domain. For the domain of cultural variations in interpersonal communication, no ontological model exists. This paper presents the first such ontological model, called AMOn+, which defines cultural variations and enables tagging culture-related mentions in textual content. AMOn+ is designed based on a novel interdisciplinary approach that combines theoretical models of culture with crowdsourced knowledge (DBpedia). An evaluation of AMOn+ demonstrated its fitness-for-purpose regarding domain coverage for annotating culture-related concepts mentioned in text corpora. This ontology can underpin computational models for making sense of UGC.
    URI
    http://hdl.handle.net/10454/10246
    Version
    Accepted Manuscript
    Citation
    Thakker D, Karanasios S, Blanchard E et al (2016) Ontology for cultural variations in interpersonal communication: building on theoretical models and crowdsourced knowledge. Journal of the Association for Information Science and Technology. 68(6): 1411-1428.
    Link to publisher’s version
    http://dx.doi.org/ 10.1002/asi.23824
    Type
    Article
    Collections
    Engineering and Informatics Publications

    entitlement

     
    DSpace software (copyright © 2002 - 2019)  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.