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The early bird catches the term: combining twitter and news data for event detection and situational awareness
BACKGROUND: Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. They can therefore be highly useful for event detection and situational awareness applications. RESULTS: In this...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5055729/ https://www.ncbi.nlm.nih.gov/pubmed/27717403 http://dx.doi.org/10.1186/s13326-016-0103-z |
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author | Thapen, Nicholas Simmie, Donal Hankin, Chris |
author_facet | Thapen, Nicholas Simmie, Donal Hankin, Chris |
author_sort | Thapen, Nicholas |
collection | PubMed |
description | BACKGROUND: Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. They can therefore be highly useful for event detection and situational awareness applications. RESULTS: In this paper we apply customised filtering techniques to existing bio-surveillance algorithms to detect localised spikes in Twitter activity, showing that these correspond to real events with a high level of confidence. We then develop a methodology to automatically summarise these events, both by providing the tweets which best describe the event and by linking to highly relevant news articles. This news linkage is accomplished by identifying terms occurring more frequently in the event tweets than in a baseline of activity for the area concerned, and using these to search for news. We apply our methods to outbreaks of illness and events strongly affecting sentiment and are able to detect events verifiable by third party sources and produce high quality summaries. CONCLUSIONS: This study demonstrates linking event detection from Twitter with relevant online news to provide situational awareness. This builds on the existing studies that focus on Twitter alone, showing that integrating information from multiple online sources can produce useful analysis. |
format | Online Article Text |
id | pubmed-5055729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50557292016-10-19 The early bird catches the term: combining twitter and news data for event detection and situational awareness Thapen, Nicholas Simmie, Donal Hankin, Chris J Biomed Semantics Research BACKGROUND: Twitter updates now represent an enormous stream of information originating from a wide variety of formal and informal sources, much of which is relevant to real-world events. They can therefore be highly useful for event detection and situational awareness applications. RESULTS: In this paper we apply customised filtering techniques to existing bio-surveillance algorithms to detect localised spikes in Twitter activity, showing that these correspond to real events with a high level of confidence. We then develop a methodology to automatically summarise these events, both by providing the tweets which best describe the event and by linking to highly relevant news articles. This news linkage is accomplished by identifying terms occurring more frequently in the event tweets than in a baseline of activity for the area concerned, and using these to search for news. We apply our methods to outbreaks of illness and events strongly affecting sentiment and are able to detect events verifiable by third party sources and produce high quality summaries. CONCLUSIONS: This study demonstrates linking event detection from Twitter with relevant online news to provide situational awareness. This builds on the existing studies that focus on Twitter alone, showing that integrating information from multiple online sources can produce useful analysis. BioMed Central 2016-10-07 /pmc/articles/PMC5055729/ /pubmed/27717403 http://dx.doi.org/10.1186/s13326-016-0103-z Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Thapen, Nicholas Simmie, Donal Hankin, Chris The early bird catches the term: combining twitter and news data for event detection and situational awareness |
title | The early bird catches the term: combining twitter and news data for event detection and situational awareness |
title_full | The early bird catches the term: combining twitter and news data for event detection and situational awareness |
title_fullStr | The early bird catches the term: combining twitter and news data for event detection and situational awareness |
title_full_unstemmed | The early bird catches the term: combining twitter and news data for event detection and situational awareness |
title_short | The early bird catches the term: combining twitter and news data for event detection and situational awareness |
title_sort | early bird catches the term: combining twitter and news data for event detection and situational awareness |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5055729/ https://www.ncbi.nlm.nih.gov/pubmed/27717403 http://dx.doi.org/10.1186/s13326-016-0103-z |
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