Analysis of Automatic Online Lead User Identification

Lead user identification is a systematic approach to uncovering product development opportunities by identifying lead users, individuals or groups actively involved in modifying or developing products for personal benefit. In this paper, a systematic approach called Fast Lead User IDentification (FLUID) based on online data mining, specifically of the Twitter micro-blogging site, is proposed. Topic classification, sentiment and intent of a given tweet or user-metadata can be automatically determined using various text mining techniques. The described FLUID system makes use of such techniques to rank retrieved users based on indexes derived from well-established lead user characteristics. In the initial analysis phase collection of relevant artifacts and contextual inquiry allow for measuring impact of each index toward delineating lead users from other non-lead users. Through refinement based on statistical analysis of expert assessments the effectiveness of the FLUID system is optimized.

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