Real-Time Detection Tracking and Monitoring of Automatically Discovered Events in Social Media (2).pdf (221.46 kB)
Download fileReal-time detection, tracking, and monitoring of automatically discovered events in social media
conference contribution
posted on 2014-12-09, 12:04 authored by Miles Osborne, Sean Moran, Richard McCreadie, Alexander Von Lunen, Martin SykoraMartin Sykora, Elizabeth Cano, Neil Ireson, Craig MacDonald, Iadh Ounis, Yulan He, Tom JacksonTom Jackson, Fabio Ciravegna, Ann O'BrienWe introduce ReDites, a system for realtime
event detection, tracking, monitoring
and visualisation. It is designed to assist
Information Analysts in understanding
and exploring complex events as they
unfold in the world. Events are automatically
detected from the Twitter stream.
Then those that are categorised as being
security-relevant are tracked, geolocated,
summarised and visualised for the
end-user. Furthermore, the system tracks
changes in emotions over events, signalling
possible flashpoints or abatement.
We demonstrate the capabilities of ReDites
using an extended use case from the
September 2013 Westgate shooting incident.
Through an evaluation of system latencies,
we also show that enriched events
are made available for users to explore
within seconds of that event occurring.
Funding
This work was funded by EPSRC grant EP/L010690/1. MO also acknowledges support from grant ERC Advanced Fellowship 249520 GRAMPLUS.
History
School
- Business and Economics
Department
- Business
Published in
The 52nd annual meeting of the Association for Computational Linguistics (ACL)Pages
59 - ?Citation
OSBORNE, M. ... et al, 2014. Real-time detection, tracking, and monitoring of automatically discovered events in social media. IN: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 23rd-24th June 2014, Baltimore, Maryland, USA. Association for Computational Linguistics, pp. 37-42.Publisher
Association for Computational Linguistics / © The AuthorsVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2014Notes
This conference paper was presented at The 52nd Annual Meeting of the Association for Computational Linguistics.ISBN
9781941643006Publisher version
Language
- en