Tweeting about public transit - Gleaning public perceptions from a social media microblog

Capturing public perceptions regarding transit systems is an essential part of creating a just and equitable service. Gathering such perceptions also holds the potential for identifying ways of increasing ridership and for identifying sources of transport-related social exclusion. Traditionally, these perceptions have been obtained from public participatory forums or via surveys on users' opinions. However, increasingly, the use of alternative methods of obtaining public perceptions has included media and social media sources. Twitter is one such social media source and it is used in this research to obtain public opinions regarding a bus rapid transit system (BRT). Rather than relying upon purely automated data mining techniques for analyzing Twitter feeds, a traditional qualitative research design is used featuring a two-step process. First, a text mining procedure is used on the Twitter feeds filtered out by keywords relevant to the transit system, and secondly, a structured content analysis is applied to the entries. This method is applied to a case study on a Bus Rapid Transit system in Cali, Colombia. The results highlight concerns with safety, problems with the system's infrastructure, and behavioral issues on the bus as primary points of discussion.