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- W2396544579 abstract "Human resources are one of the most essential elements of an organization. In particular, the more closed a group is, the higher the value each member has. Previous studies have focused on personal attributes of individual, such as medical history, and have depended upon self-diagnosis to manage structures. However, this method has weak points, such as the timeconsuming process required, the potential for concealment, and non-disclosure of participants' mental states, as this method depends on self-diagnosis through extensive questionnaires or interviews, which is solved in an interactive way. It also suffers from another problem in that relations among people are difficult to express. In this paper, we propose a multi-faced diagnosis model based on social network analysis which overcomes former weaknesses. Our approach has the following steps : First, we reveal the states of those in a social network through 9 questions. Next, we diagnose the social network to find out specific individuals such as victims or leaders using the proposed algorithm. Experimental results demonstrated our model achieved 0.62 precision rate and identified specific people who are not revealed by the existing methods." @default.
- W2396544579 created "2016-06-24" @default.
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- W2396544579 date "2015-06-15" @default.
- W2396544579 modified "2023-09-26" @default.
- W2396544579 title "Diagnosis Model for Closed Organizations based on Social Network Analysis" @default.
- W2396544579 doi "https://doi.org/10.5626/ktcp.2015.21.6.393" @default.
- W2396544579 hasPublicationYear "2015" @default.
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