Social-Semantic Analysis of Social Media Interactions to Assess Customer Satisfaction in Transit Agencies

The aim of this proposed study is to advance the discipline of social media analytics and its application to public fleet decision makers. The project starts by integrating incoming social media feeds vis-a-vis public fleets and merges all incoming data into one cloud-platform. This platform will enable (in the future) an artificially intelligent response mechanism for fleet action, including dispatching additional vehicles or communicating with consumers regarding their challenges on the street in hailing, riding or commuting by public vehicles in a public mobility system. The immediate outcome of this social media analytics tool is a better capture of customer views and opinion dynamics, customer satisfaction and operational support. This can help public  or private fleet operators at two main levels:

  1. Enhancing agency ability to model and assess customer satisfaction levels much faster and;
  2. Supporting the development of more effective two-way communications between agency and riders.

Project Partners:

Industry

Calgary Transit SP North America

Academic

University of Toronto York University University of Calgary