Data Science Journal (Mar 2007)

Multi-data Mining for Understanding Leadership Behavior

  • Naohiro Matsumura,
  • Yoshihiro Sasaki

DOI
https://doi.org/10.2481/dsj.6.S61
Journal volume & issue
Vol. 6

Abstract

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We propose an approach for understanding leadership behavior in dot-jp, a non-profit organization, by analyzing heterogeneous multi-data composed of questionnaires and mailing list archives. Attitudes toward leaders were obtained from the questionnaires, and human networks were extracted from the mailing list archives. By integrating the results, we discovered that leaders must receive messages from other people as well as send messages to construct reliable relationships.

Keywords