This research was conducted by Lizzy Da Rocha Bazilio in collaboration with AI Team, Urban Innovation and R&D, City of Amsterdam.
Involved civil servants: Iva Gornishka & Cláudia Pinhão.
Supervisors: Iva Gornishka & Clemencia Siro
MSc Thesis - UvA - Aspect- and Sentiment based Opinion Summarization of Online Reviews for Information Provision about Venue Accessibility - Lizzy Da Rocha Bazilio
MSc Thesis by Lizzy Da Rocha Bazilio
Persons with reduced mobility (PRM) have difficulties determining whether they can access venues, due to inadequate information about venues’ accessibility. Previous research has largely used computer vision techniques for this purpose and general accessibility-scores have been provided. However, due to the variety of PRM, both approaches lack user experiences that can provide detailed information on venue accessibility. Existing research has not yet investigated online reviews to obtain accessibility-related information. Therefore, we will apply text analysis to online reviews for information provision about accessibility.
The contributions of this research are three-fold. First of all, we provide an overview of information from user experiences about the accessibility of venues for PRM, as opposed to a general score or assessment. Secondly, we apply an approach to information provision for venue accessibility that has not yet been used. Namely, text analysis with NLP techniques, as opposed to the previously implemented computer vision techniques on images. Thirdly, we take multiple existing models that have been utilized for online review analyses and apply them to a new domain of reviews. We will determine what models perform best for accessibility texts.
Additional info
Image credits
Header image: Banner - Amsterdam for All - by Claudia Pinhao
Icon image: Icon - Venue Accessibility Profile - by Claudia Pinhao