| Title | Real world city event extraction from Twitter data streams |
|---|---|
| ID_Doc | 43253 |
| Authors | Zhou, YC; De, S; Moessner, K |
| Title | Real world city event extraction from Twitter data streams |
| Year | 2016 |
| Published | |
| Abstract | The immediacy of social media messages means that it can act as a rich and timely source of real world event information. The detected events can provide a context to observations made by other city information sources such as fixed sensor installations and contribute to building 'city intelligence'. In this work, we propose a novel unsupervised method to extract real world events that may impact city services such as traffic, public transport, public safety etc., from Twitter streams. We also develop a named entity recognition model to obtain the precise location of the related events and provide a qualitative estimation of the impact of the detected events. We apply our developed approach to a real world dataset of tweets collected from the city of London. (C) 2015 The Authors. Published by Elsevier B.V. |
| https://doi.org/10.1016/j.procs.2016.09.069 |
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