A methodology for analyzing web-based qualitative data

• 成果类型: Article; Proceedings Paper
• 署名作者: Romano, NC Jr; Donovan, C; Chen, HC; Nunamaker, JF Jr
• 署名单位: Oklahoma State University System; Oklahoma State University - Stillwater; University of Arizona; Cisco Systems Inc; Cisco USA; Cisco Systems Inc; Cisco USA
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• 发表日期: 2003
• 页码: 213-246
• 关键词: consumer attitudes; sales forecasts; purchase; discussions; INFORMATION; internet; models; SYSTEM

摘要

The volume of qualitative data (QD) available via the Internet is growing at an increasing pace and firms are anxious to extract and understand users' thought processes, wants and needs, attitudes, and purchase intentions contained therein. An information systems (IS) methodology to meaningfully analyze this vast 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. Outcomes include information (relationships), knowledge (patterns), and wisdom (principles) explained through visualizations and drill-down capabilities. First we present the generic methodology and then discuss an example employing it to analyze free-form comments from potential consumers who viewed soon-to-be-released film trailers provided that illustrates how the methodology and tools can provide rich and meaningful affective, cognitive, contextual, and evaluative information, knowledge, and wisdom. The example revealed that qualitative data analysis (QDA) accurately reflected film popularity. A finding is that QDA also provided a predictive measure of relative magnitude of film popularity between the most popular film and the least popular one, based on actual first week box office sales. The methodology and tools used in this preliminary study illustrate that value can be derived from analysis of Internet-based QD and suggest that further research in this area is warranted.