A Time Series Structure Analysis Method of a Meeting Using Text Data and a Visualization Method of State Transitions View Full Text


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Article Info

DATE

2019-01

AUTHORS

Ryotaro Okada, Takafumi Nakanishi, Yuichi Tanaka, Yutaka Ogasawara, Kazuhiro Ohashi

ABSTRACT

In this paper, we present a time series structure analysis method of a meeting using text data and a method for the visualization of state transitions. Our method evaluates and visualizes the convergence/divergence of the meeting in a time series using text data from the meeting. It is important to facilitate and review meetings for improving efficiency. Therefore, it is important not only to review the final agreement and conclusion in the dialogue during the meeting but also to understand the dialogue process. We introduce two indicators: freshness and representativeness. Our system expresses the status of the meeting in four quadrants (“stagnation”, “exploration”, “deepening”, and “consensus building”) corresponding to the combination of degrees of freshness and representativeness. By conducting an analysis using these indicators, we can objectively find which parts of the dialogue stagnated or advanced the discussion. In addition, it is possible to clarify the meeting process as a structure for review and facilitation, thereby improving efficiency of the meeting. Thus, we implemented a system that realizes this method. Furthermore, we applied this system to real data gathered from meetings consisting of actual multi-company members and verified its effectiveness. More... »

PAGES

1-25

References to SciGraph publications

  • 2018. A Topic Structuration Method on Time Series for a Meeting from Text Data in SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING
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    http://scigraph.springernature.com/pub.10.1007/s00354-018-0050-6

    DOI

    http://dx.doi.org/10.1007/s00354-018-0050-6

    DIMENSIONS

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