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    Automated Web issue analysis: A nurse prescribing case study

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    Authors
    Thelwall, Mike
    Thelwall, Saheeda
    Fairclough, Ruth
    Issue Date
    2006
    
    Metadata
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    Abstract
    Web issue analysis, a new automated technique designed to rapidly give timely management intelligence about a topic from an automated large-scale analysis of relevant pages from the Web, is introduced and demonstrated. The technique includes hyperlink and URL analysis to identify common direct and indirect sources of Web information. In addition, text analysis through natural language processing techniques is used identify relevant common nouns and noun phrases. A case study approach is taken, applying Web issue analysis to the topic of nurse prescribing. The results are presented in descriptive form and a qualitative analysis is used to argue that new information has been found. The nurse prescribing results demonstrate interesting new findings, such as the parochial nature of the topic in the UK, an apparent absence of similar concepts internationally, at least in the English-speaking world, and a significant concern with mental health issues. These demonstrate that automated Web issue analysis is capable of quickly delivering new insights into a problem. General limitations are that the success of Web issue analysis is dependant upon the particular topic chosen and the ability to find a phrase that accurately captures the topic and is not used in other contexts, as well as being language-specific.
    Citation
    Information Processing & Management, 42 (6): 1471-1483
    Publisher
    Elsevier
    Journal
    Information Processing & Management
    URI
    http://hdl.handle.net/2436/26893
    DOI
    10.1016/j.ipm.2006.03.011
    Additional Links
    http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VC8-4JYTS1B-1&_user=1644469&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000054077&_version=1&_urlVersion=0&_userid=1644469&md5=5c73e3382e7e6d0d7a4f4062263b4f3f
    Type
    Journal article
    Language
    en
    ISSN
    03064573
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ipm.2006.03.011
    Scopus Count
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    Research Institute in Information and Language Processing

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