Understanding Attitudes and Perceptions of Public Transport: Investigation Through Social Media and Conceptual Analysis

The ways in which people think and how they feel about different travel options play a large role in determining their transportation choices. While it is clear that in many situations people prefer to use automobiles instead of public transport, there is a lack of understanding as to the attitudes that drive people to do so, especially when public transport presents tangible benefits. Understanding these issues is extremely important, particularly considering the deleterious effects of automobile dependence, such as anthropogenic climate change. This study seeks to investigate attitudes and perceptions about public transport through examination of social media data, specifically from Twitter. A tool called Massmine is used to extract large Twitter datasets on a daily basis over the course of approximately two months. An artificial neural network-based conceptual analysis tool called Catpac is then used to extract relevant attitudinal and perceptual data from these datasets. There are two major findings from this project: First, the data obtained over the course of this study suggest that public transport users who express opinions on social media are often driven to do so by social aspects of public transport use, i.e. other people. Second, this study advances the viability of a novel method for observing attitudes and perceptions via social media. Possible avenues for targeted improvements to public transport services are then suggested. Finally, this thesis proposes several directions for future research, both in learning more about public transport via social media, as well as in applying the methodology here used to other spheres of urban life.