Artificial Intelligence Lab, Department of MIS, University of Arizona / We propose a methodology to collect, quantify and visualize qualitative consumer data. We employ a Web-based Group Support
System (GSS), GSw,b, to elicit free-form comments and a prototype comment analysis support system to facilitate comment
classification, categorization and visualization to measure attitudes. We argue that such a methodology is needed due to the
proliferation of qualitative data, the limitations of qualitative data analysis and the dearth of methods to measure attitudes
contained within free-form comments. We conducted two experiments to compare our methodology with two long-established
traditional methods, Likert scale evaluations and first-week box office sales records. We found that our methodology provides
equivalent and superior affective and evaluative attitude information, compared to Likert scale ratings. We also found that
comment analysis more accurately reflected actual first-week box office sales than did Likert scale ratings. Comment analysis
with the prototype tool was seventy-five percent more efficient than manual coding. We designed the prototype to generate
visualizations to make sense of multiple attitude dimensions through at-a-glance understanding and comparative presentation.
The methodology we propose overcomes drawbacks often associated with qualitative data analysis and offers marketers and
researchers a method to measure attitudes from free-form comments. The results indicate that qualitative data in the form of freeform
comments may be quantified and visualized to provide meaningful attitude assessment. Finally, we present future research
directions to enhance data collection and the comment analysis support system.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105275 |
| Date | January 2000 |
| Creators | Romano, Nicholas C., Bauer, Christina, Chen, Hsinchun, Nunamaker, Jay F. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Journal Article (Paginated) |
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