Persistent Link:
http://hdl.handle.net/10150/105374
Title:
A methodology for analyzing Web-based qualitative data
Author:
Romano, Nicholas C.; Donovan, Christina; Chen, Hsinchun; Nunamaker, Jay F.
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
Issue Date:
2003
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105374
Submitted date:
2004-10-01
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
Keywords:
World Wide Web; Information Systems; Qualitative Research
Local subject classification:
National Science Digital Library; NSDL; Artificial intelligence lab; AI lab

Full metadata record

DC FieldValue Language
dc.contributor.authorRomano, Nicholas C.en_US
dc.contributor.authorDonovan, Christinaen_US
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorNunamaker, Jay F.en_US
dc.date.accessioned2004-10-01T00:00:01Z-
dc.date.available2010-06-18T23:24:27Z-
dc.date.issued2003en_US
dc.date.submitted2004-10-01en_US
dc.identifier.citationA methodology for analyzing Web-based qualitative data 2003, 19(4):213-246 Journal of Management Information Systemsen_US
dc.identifier.urihttp://hdl.handle.net/10150/105374-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractThe 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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.subjectWorld Wide Weben_US
dc.subjectInformation Systemsen_US
dc.subjectQualitative Researchen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.titleA methodology for analyzing Web-based qualitative dataen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalJournal of Management Information Systemsen_US
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