Analyzing spread of influence in social networks for transportation applications

The spread of influence on social networks has been extensively studied but has been primarily demonstrated on large networks such as author collaboration networks. It is not clear how well these approaches translate to real-world social networks comprised of users discussing region-specific topics related to transportation. This work attempts to utilize the concept of influence in social media to identify the individuals who exert the most influence on transportation-related topics. The work describes a web-accessible system that enables a user to select transportation-related topics and then retrieve in real-time the most influential potential influential individuals and/or organizations on Twitter with respect to that specific topic. Influence is quantified using two simple measures of influence, the number of Twitter mentions and the number of retweets of a message. The locations of these influential entities are then indicated on a web-accessible front-end using Google Maps. Such a tool can eventually be used for many purposes including limiting misinformation and encouraging acceptance of a new transportation products or service.