{"title":"理解领导行为的多数据挖掘","authors":"N. Matsumura, Yoshihiro Sasaki","doi":"10.2481/dsj.6.S61","DOIUrl":null,"url":null,"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.","PeriodicalId":35375,"journal":{"name":"Data Science Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-data Mining for Understanding Leadership Behavior\",\"authors\":\"N. Matsumura, Yoshihiro Sasaki\",\"doi\":\"10.2481/dsj.6.S61\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":35375,\"journal\":{\"name\":\"Data Science Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data Science Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2481/dsj.6.S61\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Science Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2481/dsj.6.S61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}
Multi-data Mining for Understanding Leadership Behavior
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.
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.