Abstract
3A.004 Internet-based textual big data and road traffic injuries
Injury prevention, Vol.27(Suppl 2), pp.A21-A22
03/2021
DOI: 10.1136/injuryprev-2021-safety.65
Abstract
BackgroundInternet-based big data may offer important and timely information concerning road traffic injury data, supplementing official government statistics. We developed computer-based approaches to define, extract and automatically collect internet-based Chinese language big data on road traffic injuries.MethodsBased on injury prevention matrices and ICD-10, we established a thesaurus set and analysis framework for data extraction. A dilated convolutions neural network classifier was developed to filter eligible news stories based on 10,000 researcher-annotated news sources, and algorithms were built to extract information concerning relevant variables. Word frequency was reported using a Python Chinese word segmentation module (Jieba). Pearson correlation coefficients examined relations between internet-based big data and official statistics.Results650,140 media reports were captured from 27 Chinese news websites, and 92,813 news pieces were filtered as eligible reports (accuracy=86%). Searches captured information about 71,829 traffic crashes from January 2013-September 2019. The words ‘crash’, ‘vehicle’ and ‘scene’ were the most frequently used words in the stories. Our results revealed characteristics that official statistics did not cover, such as changes in travel patterns for the elderly. The number of media-reported crashes was highly correlated with official statistics (r=0.84, p=0.035).ConclusionInternet-based big data offers information about traffic crashes that can supplement official government statistics and aid in road traffic injury prevention strategies. Extension to countries where government data and statistics are unreliable, but news reporting is reliable, appeals in particular.Learning OutcomesInternet-based big data offers data that can supplement existing road traffic injury sources and guide prevention efforts.
Details
- Title: Subtitle
- 3A.004 Internet-based textual big data and road traffic injuries
- Creators
- Peixia Cheng - Central South UniversityJianxin Wang - Central South UniversityWangxin Xiao - Central South UniversityDavid Schwebel - University of Alabama at BirminghamPeishan Ning - Central South UniversityYue Wu - Central South UniversityGuoqing Hu - Central South University
- Resource Type
- Abstract
- Publication Details
- Injury prevention, Vol.27(Suppl 2), pp.A21-A22
- DOI
- 10.1136/injuryprev-2021-safety.65
- ISSN
- 1353-8047
- eISSN
- 1475-5785
- Publisher
- BMJ PUBLISHING GROUP; LONDON
- Language
- English
- Date published
- 03/2021
- Academic Unit
- Research Administration
- Record Identifier
- 9984958615302771
Metrics
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