Multi-taxonomy: Determining Perceived Brand Characteristics from Web Data

  • Authors:
  • Scott Spangler;Larry Proctor;Ying Chen

  • Affiliations:
  • -;-;-

  • Venue:
  • WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
  • Year:
  • 2008

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Abstract

A strong brand is a major asset to any corporation. Traditional brand image and reputation tracking is limited to news wires and contact centers analysis. However, with the emergence of web, Consumer Generated Media (CGM), such as blogs, news forums, message boards, and web pages/sites, is rapidly transforming the way companies analyze their brand perceptions. This paper describes the next generation COBRA (Corporate Brand and Reputation Analysis) approach to mining a wide range of CGM content to discover how the social media-based community perceives the brand. The solution processes a diverse set of structured and unstructured information and mines CGM content by generating multiple taxonomies from the data. These taxonomies are then used singly and in combination to better understand important brand characteristics and hence enhance marketing and strategic decision making. We illustrate our approach with a real-world case study involving the Kraft Foods’ Vegemite brand.