Thesis Code: 23003

Thesis Type: M.Sc. thesis in Computer Science, ICT for Smart Societies

Research Domain: Future Cities & Communities

• Experience with Python
• Interest in Natural Language Processing
• Skills in descriptive and inferential statistics and in the use of statistical softwares
• Skills on data science (analysis and processing)
• Ability to represent data

For a technology to be widely accepted by the public, it is not enough that it brings benefits. The public needs also to be highly involved in order to understand whether to use new technology. According to several research studies, at present, the level of awareness and understanding of UAM (Unmanned Air Mobility) / UAV (Unmanned Air Vehicles) is very low among people.
The objective of this thesis is to assess the public acceptance of UAV/UAM using statistical models (e.g. UTAUT, TRA, TPB) or by mining social data with text mining / machine learning algorithms related to natural language processing.
Firstly, the candidate will carry out a review of public acceptance evaluation methods with respect to UAV/UAM, defining: domains of application of UAV/UAM, main constraints recognised by the general public, and effective strategies to foster the public acceptance. Then, the candidate will assess public acceptance. The candidate will have both the task of collecting and evaluating the data of the case study. Such a data-driven approach could be helpful to measure community awareness and engagement around UAM/UAV-related topics. Findings can constitute policy insights for those cities and regions that are already equipping themselves to introduce air mobility services.
The thesis will be carried out in collaboration between LINKS and the University of Turin.

Contact: send a resume with attached the list of exams to specifying the thesis code and title.