European Transport Conference 2023: Winner of the Jacobs Award
ETC 2023: JACOBS AWARD
We are delighted to announce the winner of the "Jacobs Award for Paper Demonstrating the Most Innovative use of Data". Our sincere congratulations go to Xuefen Cai for her paper titled:
'An Integrated Framework of Social Media Opinion Mining and Category System to Analyse Public Opinion Towards Transportation Technology and Services'.
Thank you to the team at Jacobs, lead by Prutha Shah, Sedil Kilic and Sadie Langdon who noted:
“We selected this paper as the winner because it impressed the judges at each stage of the selection process. This study used social media posts, collected using social media mining by unsupervised machine learning models, with the aim to collect data on people’s opinions on autonomous vehicles.
The social media posts are categorised from ‘very positive’ to ‘very negative’, which not only shows the volume of social media mentions, but also paints a picture of how well-received autonomous vehicles are by the public. The outcome of this study is proving to be promising and can be extended to the field of transportation operations or policy-making to understand user perceptions towards the AV, user adoption and acceptance over time and to identify areas for improvements.
In our shortlist, there were some impressive papers that made the final choice very difficult. Several papers demonstrated really innovative use of data, however, it was the unique data collection technique and its potential to improve and expand in the future that made us choose this paper as the winner".
To learn more about the awards at ETC please and be considered for presenting your paper at ETC 2024, please go to www.aetransport.org
We hope to see you in Antwerp next year!
Award Winner Xuefen has more than 15 years of work experience in LTA and has contributed in the field of traffic design and management, ITS development, ITS standards, data quality, governance and management, and business intelligence analytics. She has been involved in several transport computational research such as the social media sentiment analysis and topic modelling on users’ perceptions towards autonomous vehicles, data fusion techniques (LSTM and multiple linear regression algorithm) and free-flow speed estimation techniques (maximum-likelihood estimation) in ITS. She is also an Institution of Engineers, Singapore (IES) Chartered Engineer (Transportation). Ms Xuefen Cai, MSc(Eng), MIES, CEng(SG) Manager, Intelligent Transport Systems Development (TT) Assistant Chief Specialist, Intelligent Transport Methodologies, Road and Traffic Specialists |  |
