TY - GEN
T1 - The mindMine comment analysis tool for collaborative attitude solicitation, analysis, sense-making and visualization
AU - Romano, Nicholas C.
AU - Bauer, Christina
AU - Packard, Hewlett
AU - Chen, Hsinchun
AU - Nunamaker, Jay F.
N1 - Publisher Copyright:
© 2000 IEEE
PY - 2000
Y1 - 2000
N2 - This paper describes a study to explore the integration of Group Support Systems (GSS) and Artificial Intelligence (AI) technology to provide solicitation, analytical, visualization and sense-making support for attitudes from large distributed marketing focus groups. The paper describes two experiments and the concomitant evolutionary design and development of an attitude analysis process and the MindMine Comment Analysis Tool. The analysis process circumvents many of the problems associated with traditional data gathering via closed-ended questionnaires and potentially biased interviews by providing support for online free response evaluative comments. MindMine allows teams of raters to analyze comments from any source, including electronic meetings, discussion groups or surveys, whether they are Web-based or same-place. The analysis results are then displayed as visualizations that enable the team quickly to make sense of attitudes reflected in the comment set, which we believe provide richer information and a more detailed understanding of attitudes.
AB - This paper describes a study to explore the integration of Group Support Systems (GSS) and Artificial Intelligence (AI) technology to provide solicitation, analytical, visualization and sense-making support for attitudes from large distributed marketing focus groups. The paper describes two experiments and the concomitant evolutionary design and development of an attitude analysis process and the MindMine Comment Analysis Tool. The analysis process circumvents many of the problems associated with traditional data gathering via closed-ended questionnaires and potentially biased interviews by providing support for online free response evaluative comments. MindMine allows teams of raters to analyze comments from any source, including electronic meetings, discussion groups or surveys, whether they are Web-based or same-place. The analysis results are then displayed as visualizations that enable the team quickly to make sense of attitudes reflected in the comment set, which we believe provide richer information and a more detailed understanding of attitudes.
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M3 - Conference contribution
AN - SCOPUS:85094125128
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
BT - Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, HICSS 2000
PB - IEEE Computer Society
T2 - 33rd Annual Hawaii International Conference on System Sciences, HICSS 2000
Y2 - 4 January 2000 through 7 January 2000
ER -