# A C-BiLSTM Approach to Classify Construction Accident Reports
## 1 Introduction  
Workplace health and safety is a significant concern in all countries [1] because there are more than 2.78 million deaths caused by occupational accidents every year according to the International Labour Organization [2]. The construction industry is recognized as the most hazardous one among various industries [3]. In the United States, construction accounts for approximately one-sixth of fatal accidents while only employing 7% of the national workforce, and there are four recorded injuries per 100 full-time construction workers in the construction industry. Construction accidents usually result in both health/safety issues and financial loss [4], and thus there has been abundant research motivated by the alarming injury and fatality rates. Research on construction safety is mainly conducted from two perspectives: it is either management-driven or technology-driven [5]. In general, it is assumed that enhanced construction safety management can effectively improve on-site safety performance and reduce the number of accidents. Research from the management perspective usually includes either safety management processes such as safety education and training or focuses on individual/organizational characteristics such as workers' attitudes towards safety. However, the effect of traditional strategies for preventing injuries was limited due to theirreactive and regulatory-based nature [6]. [PERSON] and [PERSON] [7] indicate that the construction industry has reached saturation with respect to these injury prevention strategies. Along with the advancement of information and communication technology, various innovative technologies have been investigated to assist and improve on existing management-driven safety management practices. These technical approaches aimed to enhance rather than replace management efforts [8]. Besides the assistance of technologies, some new injury prevention strategies have been developed for the construction industry. The risk analysis method is one of them which are used in safety programs to improve safety performance. For example, [PERSON] and [PERSON] [9] compared the risk of different building trades, [PERSON] and [PERSON] [10] quantified the safety risk for various activities required to construct concrete formwork, and [PERSON] and [PERSON] [11] studied the impact of tower cranes on job site safety. However, most of these risk-based studies are limited to specific application fields and hard to translate well to a general scope of the construction industry. To address this limitation in the previous literature, [PERSON] and [PERSON] [12] proposed an attribute-based risk identification and analysis method that helps designers to identify and model the safety risk independently of specific activities or trades. In this method, accidents are considered the outcome of interaction among physical conditions of the jobsite, environmental factors, administrative issues, and human error. Although this method shows promise, it requires the analysis of large numbers of construction injury reports to first classify the causes and then see patterns and trends that emerge from the data. Such manual content analysis is laborious and resource-intensive [13]. It is vitally important to analyze past accidents and understand the causes to prevent the occurrence of similar accidents and promote workplace safety [14] by removing or reducing the identified causes. Construction injury reports contain a wealth of empirical knowledge that could be used to better understand, predict, and prevent the occurrence of construction accidents. Some major construction companies and federal agencies, for example, the Occupational Safety and Health Administration (OSHA), possess those reports in the form of huge digital databases. Because different companies have different requirements for the forms of accident reports, these reports are often unstructured or semi-structured. The first step towards the effective analysis of construction injury reports is the rigorous classification based on accident causes.