Generating demand responsive bus routes from social network data analysis

Many European cities are establishing mandatory obligations for large mobility demand generators such as business and retail parks, tourist sites and events to develop Mobility Management Plans (MMP). Developing MMPs for events with uncertain spatial demand is a particular challenge. This paper investigates whether reliable demand data can be extracted from mining social network (Twitter) content and using the resulting information to inform the design of commercially viable bus routes from peri-urban areas of Barcelona to a large music event (Canet Rock). Using data from relevant Twitter users, a Twitter influence score was established for each of the 947 municipalities in the Barcelona Region, providing a spatially distributed picture of the demand to attend the event, prior to event ticket purchase. This was used as the basis for planning and delivering 11 new commercially viable event bus routes transporting over 450 additional passengers from peri-urban and more rural areas in the Barcelona Region. This paper demonstrates that the innovation of information mining from Social Networks can provide better comprehension of the demand to support Mobility Management Planning for large events and can radically improve the ability of bus services to serve demand from peri-urban and rural areas.

Automated summary

This paper explores the use of social network data from Twitter to extract reliable demand information for planning commercially viable bus routes to a large music event in Barcelona. By analyzing Twitter influence scores for municipalities in the region, the study successfully identified demand patterns and facilitated the creation of 11 new bus routes that transported over 450 additional passengers from peri-urban and rural areas. This innovative approach demonstrates the potential for social network mining to enhance Mobility Management Planning for large events and improve bus services for rural and peri-urban areas.