ITM Web Conf.
Volume 36, 2021The 16th IMT-GT International Conference on Mathematics, Statistics and their Applications (ICMSA 2020)
|Number of page(s)
|Statistics and Data Science
|26 January 2021
Underreporting traffic accidents in Malaysia – a sentiment analysis
Department of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Malaysia
* Corresponding author: firstname.lastname@example.org
The underreporting scenario is claimed to be the source of the extra zeros in traffic accident data. This leads to a latter problem in which the fitted statistical model may not be able to produce correct and reliable estimates. Understanding the root of problem as to what is the main cause of the underreporting scenario is essential to assist on the decision making process in traffic accident analysis. In this study, 200 Malaysian drivers were interviewed on their sentiments towards this issue. Their opinions on the causes of underreporting scenario are investigated then assessed using text analyses. First, the Latent Dirichlet Allocation text modelling is employed to find the underlying themes in the reasons of not reporting a traffic accident. Then, the polarity of the topics is measured using a lexicon based sentiment analysis. Results showed that majority Malaysian drivers (80.5%) consider that reporting a minor or non-fatality accident is not important and can be neglected. The decision is due to the fact that of complicated and time consuming reporting process. The drivers are also asked on their opinion after the consequences of underreporting are informed to them. The polarity of their answers shifted to more positive in which 71% drivers will report an accident that occur in the future.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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