An interpersonal sentiment quantification method applied to work relationship prediction

Miyuki Imada, Kei Hirose, Manabu Yoshida, Sun Yong Kim, Naoya Toyozumi, Guillaume Lopez, Yutaka Kano

研究成果: ジャーナルへの寄稿総説査読


For a business to be successful, it is important for people in the business to consider how other people feel, that is, to consider interpersonal sentiment. Our research goal is to quantitatively predict the strength of interpersonal sentiment by analyzing a small amount of data on office employees, for example, their gender or age group, and data on events such as giving positive feedback on work done and sexual or power harassment without directly asking someone about their change in sentiment. In this article, we propose an interpersonal-sentiment-changing model for this quantification and propose two new analysis methods for developing prediction formulas. These methods can be used even if 90% of data is missing and in environments in which it is difficult to gather data in a comparatively short time. We also implement two visualization systems to predict how interpersonal sentiment changes for each event based on actual office data.

ジャーナルNTT Technical Review
出版ステータス出版済み - 3月 2017

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンスの応用
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学


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