• Login
    View Item 
    •   Home
    • Colleges, Departments, and Organizations
    • Digital Library of Information Science & Technology (DLIST)
    • DLIST
    • View Item
    •   Home
    • Colleges, Departments, and Organizations
    • Digital Library of Information Science & Technology (DLIST)
    • DLIST
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UA Campus RepositoryCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournal

    My Account

    LoginRegister

    About

    AboutUA Faculty PublicationsUA DissertationsUA Master's ThesesUA Honors ThesesUA PressUA YearbooksUA CatalogsUA Libraries

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    A methodology for analyzing Web-based qualitative data

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    methodology.pdf
    Size:
    28.09Mb
    Format:
    PDF
    Download
    Author
    Romano, Nicholas C.
    Donovan, Christina
    Chen, Hsinchun
    Nunamaker, Jay F.
    Issue Date
    2003
    Submitted date
    2004-10-01
    Keywords
    World Wide Web
    Information Systems
    Qualitative Research
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial intelligence lab
    AI lab
    
    Metadata
    Show full item record
    Citation
    A methodology for analyzing Web-based qualitative data 2003, 19(4):213-246 Journal of Management Information Systems
    Journal
    Journal of Management Information Systems
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105374
    Abstract
    The volume of qualitative data (QD)available via the Internet is growing at an increasing pace and firms are anxious to extract and understand user's thought processes, wants and needs, attitudes, and purchase intentions contained therein. An information systems (IS) methodology to meaningfully analyze this vase resource of QD could provide useful information, knowledge, or wisdom firms could use for a number of purposes including new product development and quality improvement, target marketing, accurate "user focused" profiling, and future sales prediction. In this paper, we present an IS methodology for analysis of Internet-based QD consisting of three steps: elicitation; reduction through IS-facilitated selection, coding, and clustering; and visualization to provide at-a-glance understanding.
    Type
    Journal Article (Paginated)
    Language
    en
    Collections
    DLIST

    entitlement

     
    The University of Arizona Libraries | 1510 E. University Blvd. | Tucson, AZ 85721-0055
    Tel 520-621-6442 | repository@u.library.arizona.edu
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    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.