Author(s)

ALEXANDROS SDOUKOPOULOS, ANASTASIA NIKOLAIDOU, MAGDA PITSIAVA-LATINOPOULOU & PANAGIOTIS PAPAIOANNOU

Abstract

Achieving sustainable urban mobility is a complex and multivariate issue that requires constant monitoring and evaluation of the existing situation and possible reconsideration and adjustment of objectives and strategy. The use of indicators is perhaps the most common methodological assessment tool for the sustainable urban mobility level achieved. Key performance indicators can provide in a simple way useful information for complex phenomena in an urban area (i.e. identification of the specific problems and their development over time). Thus, they contribute at a great degree to the decisions made concerning the prioritization of measures and policies toward achieving a goal. However, the use of indicators often constitutes a highly time consuming and costly process due to the large volumes of raw data required for their calculation. In recent years, a solution toward this problem is attempted to be given through the adoption of new technologies and approaches, such as the collection and export of ‘big data’ from social networks such as Facebook, Twitter, etc. Social networks provide to their users a continuous and enhanced ability for communication, interface and interaction. Such networks are therefore an important potential tool for the promotion of research in the transport sector, as the amount of data generated in their context gives the possibility to analyse and investigate with greater precision critical issues (e.g. trips characteristics) of urban mobility. The present study is an attempt to link the indicators related to sustainable mobility with social networks. The main advantage resulting from the above link, beyond the possibility of a more precise evaluation of the indicators, is to highlight the society’s position toward the prioritization of the various transport-related aspects and measures.

Keywords

big data, sentiment analysis, social media, sustainable urban mobility indicators, Twitter