Li, Y., Kaneria, A., Zhao, X. & Manchaiah, V.
In: N. Stanton (ed). Advances in Human Factors of Transportation. Springer Nature: Switzerland AG, pp. 341-350.
Publication year: 2020

Abstract

This study analyzed the driving behavior and accidents related to traffic accidents using twitter tweets as a tool for text mining. Sharing short real time messages on twitter is becoming a popular and powerful microblogging tool which conveys more than 400 million messages per day. Active users when encounter any traffic incidents, posts instant messages on twitter. Tweets with key word “traffic accident” were collected using Google Sheets with twitter’s legal API keys obtained for research purpose. Various analyses were on 40,000 collected tweets performed on these tweets and was represented graphically using tableau analysis software and Rstudio. This method proved to be an effective and inexpensive method to study peoples’ real time approach on traffic accident throughout the world. It proved to be a strong approach towards learning traffic accident behaviors.