The Efficacy of Mining Social Media Data for Transport Policy and Practice

Susan Grant-Muller, Ayelet Gal-Tzur, Einat Minkov, Silvio Nocera, Tsvi Kuflik, I. Shoor

Research output: Contribution to conferencePaperpeer-review

Abstract

The overarching question of whether social media (SM) can produce information of sufficient quality to meet the needs of the transport system planners and operators, policy makers and travellers forms the core of this paper. Three sub themes are investigated, focusing primarily on SM text data and the perspective of transport authorities. A typology of seven primary transport data needs, current data sources and SM sources illustrates advantages of SM data in particular contexts. Following an overview of the text mining process, a review of four main challenges this holds for the transport domain is given. These include issues concerning ontologies, sentiment analysis, location names and measuring accuracy. Finally a review of academic and soft literature has highlighted institutional issues in the use of SM concluding that potential uses of SM information have not yet been explored to their full value.
Original languageEnglish
StatePublished - 2014
Event93rd Annual Meeting of the Transportation Research Board (TRB) -
Duration: 1 Jan 2014 → …

Conference

Conference93rd Annual Meeting of the Transportation Research Board (TRB)
Period1/01/14 → …

Bibliographical note

This paper was sponsored by TRB committee ABJ50 Information Systems and Technology.

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