Multi-data Mining for Understanding Leadership Behavior

Q2 Computer Science

Data Science Journal Pub Date : 2007-03-28 DOI:10.2481/dsj.6.S61

N. Matsumura, Yoshihiro Sasaki

引用次数: 0

Abstract

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.

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理解领导行为的多数据挖掘

本文通过分析问卷调查和邮件列表档案组成的异构多数据，提出了一种理解非营利组织。jp的领导行为的方法。从问卷中获得对领导者的态度，并从邮件列表档案中提取人际网络。通过整合这些结果，我们发现领导者必须从其他人那里接收信息并发送信息，才能建立可靠的关系。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data Science Journal Computer Science-Computer Science (miscellaneous)

CiteScore

5.40

自引率

0.00%

发文量

审稿时长

10 weeks

期刊介绍： The Data Science Journal is a peer-reviewed electronic journal publishing papers on the management of data and databases in Science and Technology. Details can be found in the prospectus. The scope of the journal includes descriptions of data systems, their publication on the internet, applications and legal issues. All of the Sciences are covered, including the Physical Sciences, Engineering, the Geosciences and the Biosciences, along with Agriculture and the Medical Science. The journal publishes papers about data and data systems; it does not publish data or data compilations. However it may publish papers about methods of data compilation or analysis.