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

Research output: Contribution to journalReview articlepeer-review


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.

Original languageEnglish
JournalNTT Technical Review
Issue number3
Publication statusPublished - Mar 2017

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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