Predicting Road Accidents with Web Scraping and Machine Learning Techniques

Sinanaj, Luan; Bexheti, Lejla Abazi

doi:10.1007/978-3-031-42511-0_51

Springer Proceedings in Business and Economics

2023

DOI: 10.1007/978-3-031-42511-0_51

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Predicting Road Accidents with Web Scraping and Machine Learning Techniques

Luan Sinanaj,

Lejla Abazi Bexheti

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2023

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Cited by 1 publication

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Analysis and Visualization of Road Accidents Using Heatmaps Based on Web Data

Sinanaj,

Bexheti

2023

SEEU Review

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Road accidents have increased rapidly in recent years for a variety of reasons. Analyzing and visualizing road accidents through heatmaps can help improve policies for their prevention by informing about areas with a high-risk of road accidents. The purpose of this research is to build a model for the analysis and visualization of road accidents through heatmaps. Information about road accidents is extracted from the news of the main online media portals through scripts in the Python language and Web Scraping techniques. From the extraction of about 30,000 articles from news portals for one year, only 829 were selected in the end that provided information about road accidents. As a result, and contribution of this research, a corpus was built with the geographic coordinates of road accidents and on this data our model was applied for the analysis and visualization of high-risk areas of road accidents using heatmaps. The visualization of heatmaps was done through a Python script, where it was applied to the geographic coordinates of road accidents.

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Analysis and Visualization of Road Accidents Using Heatmaps Based on Web Data

Sinanaj,

Bexheti

2023

SEEU Review

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Predicting Road Accidents with Web Scraping and Machine Learning Techniques

Cited by 1 publication

References 12 publications

Analysis and Visualization of Road Accidents Using Heatmaps Based on Web Data

Analysis and Visualization of Road Accidents Using Heatmaps Based on Web Data

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