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Real world city event extraction from Twitter data streams

De, S, Zhou, Y and Moessner, K (2016) Real world city event extraction from Twitter data streams In: International Workshop on Data Mining on IoT Systems (DaMIS16), 2016-09-19 - 2016-09-22, London, UK.

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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.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Communcation Systems
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :
AuthorsEmailORCID
De, SUNSPECIFIEDUNSPECIFIED
Zhou, YUNSPECIFIEDUNSPECIFIED
Moessner, KUNSPECIFIEDUNSPECIFIED
Date : 21 September 2016
Identification Number : 10.1016/j.procs.2016.09.069
Copyright Disclaimer : © 2016 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license. https://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords : Smart city; Twitter; city events; event extraction
Depositing User : Symplectic Elements
Date Deposited : 22 Jul 2016 16:30
Last Modified : 27 Sep 2016 14:07
URI: http://epubs.surrey.ac.uk/id/eprint/811339

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