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.

欧洲许多城市正在为大型出行需求产生者（例如商业和零售园区，旅游景点和活动）制定强制性义务，以制定出行管理计划（MMP）。为空间需求不确定的事件开发MMP是一个特殊的挑战。

本文研究了是否可以从挖掘社交网络（Twitter）内容中提取可靠的需求数据，并使用所得信息为从巴塞罗那郊区到大型音乐活动（Canet Rock）的商业可行公交路线的设计提供信息。使用来自相关Twitter用户的数据，为巴塞罗那地区947个城市中的每个城市建立了Twitter影响力得分，从而在购买活动门票之前提供了参加活动需求的空间分布图。这被用作规划和交付11条新的商业可行的事件巴士路线的基础，该路线运送了450多名来自巴塞罗那地区郊区和更多农村地区的乘客。

本文表明，来自社交网络的信息挖掘技术的创新可以更好地理解需求，以支持大型事件的移动性管理计划，并可以从根本上提高公交服务满足郊区和农村地区需求的能力。