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A Case Study of a Text Mining Method for Discovering Evolutionary Patterns of Mobile Phone in Korea

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2015, 20(2), pp.29-45
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Byung-Won On ORD ID 1

1군산대학교

Accredited

ABSTRACT

Systematic theory, concepts, and methodology for the biological evolution have been developed whilepatterns and principles of the evolution have been actively studied in the past 200 years. Furthermore,they are applied to various fields such as evolutionary economics, evolutionary psychology, evolutionarylinguistics, making significant progress in research. In addition, existing studies have applied mainbiological evolutionary models to artifacts although such methods do not fit to them. These models are alsolimited to generalize evolutionary patterns of artifacts because they are designed in terms of a subjectivepoint of view of experts who know well about the artifacts. Unlike biological organisms, because artifactsare likely to reflect the imagination of the human will, it is known that the theory of biological evolutioncannot be directly applied to artifacts. In this paper, beyond the individual’s subjective, the aim of ourresearch is to present evolutionary patterns of a given artifact based on peeping the idea of the public. Forthis, we propose a text mining approach that presents a systematic framework that can find out theevolutionary patterns of a given artifact and then visualize effectively. In particular, based on our proposal,we focus mainly on a case study of mobile phone that has emerged as an icon of innovation in recentyears. We collect and analyze review posts on mobile phone available in the domestic market over the pastdecade, and discuss the detailed results about evolutionary patterns of the mobile phone. Moreover, thiskind of task is a tedious work over a long period of time because a small number of experts carry out anextensive literature survey and summarize a huge number of materials to finally draw a diagram ofevolutionary patterns of the mobile phone. However, in this work, to minimize the human efforts, wepresent a semi-automatic mining algorithm, and through this research we can understand how humancreativity and imagination are implemented. In addition, it is a big help to predict the future trend of mobilephone in business and industries.

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This paper was written with support from the National Research Foundation of Korea.
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