Leveraging Social Network Analysis for Enhancing Safety Reporting in the Workplace

Abstract

Unsafe Condition Reporting is an important source of information for companies to determine whether the reporting can be identified effectively as the key to reducing work accidents. This research aims to ascertain the Social Network Analysis visualization network in the context of reporting unsafe conditions in the IZAT application and categorizing data processing outcomes. The findings revealed that the data collection process yielded 26,658 data items. The Unsafe Condition content comprised 79,667 words, with 2,388 unique words identified. The average number of occurrences per word was 33.36139. Certain network property calculations can be inferred from these results. Then, the word mapping with five related topics was carried out. The results of the categorization of the unsafe condition word mapping can be used as evaluation material for companies to prevent work accidents. In particular, the network visualization results can identify the most discussed topics and social network relationships of reporting in the IZAT application.

Keywords

• Reporting
• Safety Culture
• Unsafe Condition
• Occupational Health and Safety
• Social Network Analysis