@article{ref1,
title="Real world city event extraction from twitter data streams",
journal="Procedia computer science",
year="2016",
author="Zhou, Yuchao and De, Suparna and Moessner, Klaus",
volume="98",
number="",
pages="443-448",
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.<p /> <p>Language: en</p>",
language="en",
issn="1877-0509",
doi="10.1016/j.procs.2016.09.069",
url="http://dx.doi.org/10.1016/j.procs.2016.09.069"
}