Case Study of Text Analytics Applied to Accident Reports of a University

Many accidents have occurred in universities and the accident reports are accumulated in most universities. The information described in the accident reports must be used effectively to prevent a recurrence of the accidents. In this study, we applied text analytics to the description written in 373...

Full description

Saved in:
Bibliographic Details
Published inMATEC Web of Conferences Vol. 333; p. 10003
Main Authors Hayashi, Rumiko, Yamada, Tsubasa, Shinkawa, Kouhei, Tomita, Kengo, Nishikimi, Tadashi, Murata, Shizuaki, Kurimoto, Hidekazu
Format Journal Article Conference Proceeding
LanguageEnglish
Published Les Ulis EDP Sciences 2021
Subjects
Accidents
Case studies
Human error
Mathematical analysis
Online AccessGet full text

Cover

More Information
Summary:Many accidents have occurred in universities and the accident reports are accumulated in most universities. The information described in the accident reports must be used effectively to prevent a recurrence of the accidents. In this study, we applied text analytics to the description written in 373 accident reports in a university as a case study. Information mining method was adopted for the contents analysis, and 9 factors based on m-SHEL and human error, that is “software”, “hardware”, “environment”, “liveware2”, “management” “slip”, “lapse”, “mistake”, and “violation” were used for morphological analysis for description in report. The factors in each category of accident situation were extracted, and it is suggested that text analytics is one of the most effective methods to analyse the accident reports in universities.
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/202133310003