Real-time detection, tracking, and monitoring of automatically discovered events in social media

Miles Osborne; Sean Moran; Richard McCreadie; Alexander von Lunen; Martin Sykora; Elizabeth Cano; Neil Ireson; Craig Macdonald; Iadh Ounis; Yulan He; Tom Jackson; Fabio Ciravegna; Ann O'Brien

Real-time detection, tracking, and monitoring of automatically discovered events in social media

Miles Osborne, Sean Moran, Richard McCreadie, Alexander von Lunen, Martin Sykora, Elizabeth Cano, Neil Ireson, Craig Macdonald, Iadh Ounis, Yulan He, Tom Jackson, Fabio Ciravegna, Ann O'Brien

Computer Science Research Group

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

We 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.

Original language	English
Title of host publication	The 52nd annual meeting of the Association for Computational Linguistics (ACL)
Number of pages	6
Publication status	Published - 2014
Event	52nd annual meeting of the Association for Computational Linguistics - Baltimore, MD, United States Duration: 22 Jun 2014 → 27 Jun 2014

Meeting

Meeting	52nd annual meeting of the Association for Computational Linguistics
Abbreviated title	ACL 2014
Country/Territory	United States
City	Baltimore, MD
Period	22/06/14 → 27/06/14

2 Conference publication

A simple Bayesian modelling approach to event extraction from Twitter
Zhou, D., Chen, L. & He, Y., 2014, The 52nd Annual Meeting of the Association for Computational Linguistics (ACL). Association for Computational Linguistics, Vol. 2. p. 700-705 6 p.
Research output: Chapter in Book/Published conference output › Conference publication
Automatic labelling of topic models learned from Twitter by summarisation
Cano, E. & He, Y., 2014, 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference. Association for Computational Linguistics, Vol. 2. p. 618-624 7 p.
Research output: Chapter in Book/Published conference output › Conference publication

Cite this

@inproceedings{341ca1dd7b134e6ca1db4152f7ae8ec7,

title = "Real-time detection, tracking, and monitoring of automatically discovered events in social media",

abstract = "We 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.",

author = "Miles Osborne and Sean Moran and Richard McCreadie and {von Lunen}, Alexander and Martin Sykora and Elizabeth Cano and Neil Ireson and Craig Macdonald and Iadh Ounis and Yulan He and Tom Jackson and Fabio Ciravegna and Ann O'Brien",

year = "2014",

language = "English",

isbn = "978-1-937284-73-2",

booktitle = "The 52nd annual meeting of the Association for Computational Linguistics (ACL)",

note = "52nd annual meeting of the Association for Computational Linguistics, ACL 2014 ; Conference date: 22-06-2014 Through 27-06-2014",

}

Osborne, M, Moran, S, McCreadie, R, von Lunen, A, Sykora, M, Cano, E, Ireson, N, Macdonald, C, Ounis, I, He, Y, Jackson, T, Ciravegna, F & O'Brien, A 2014, Real-time detection, tracking, and monitoring of automatically discovered events in social media. in The 52nd annual meeting of the Association for Computational Linguistics (ACL). 52nd annual meeting of the Association for Computational Linguistics, Baltimore, MD, United States, 22/06/14.

TY - GEN

T1 - Real-time detection, tracking, and monitoring of automatically discovered events in social media

AU - Osborne, Miles

AU - Moran, Sean

AU - McCreadie, Richard

AU - von Lunen, Alexander

AU - Sykora, Martin

AU - Cano, Elizabeth

AU - Ireson, Neil

AU - Macdonald, Craig

AU - Ounis, Iadh

AU - He, Yulan

AU - Jackson, Tom

AU - Ciravegna, Fabio

AU - O'Brien, Ann

PY - 2014

Y1 - 2014

N2 - We 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.

AB - We 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.

M3 - Conference publication

SN - 978-1-937284-73-2

BT - The 52nd annual meeting of the Association for Computational Linguistics (ACL)

T2 - 52nd annual meeting of the Association for Computational Linguistics

Y2 - 22 June 2014 through 27 June 2014

ER -

Real-time detection, tracking, and monitoring of automatically discovered events in social media

Abstract

Meeting

Fingerprint

Research output

A simple Bayesian modelling approach to event extraction from Twitter

Automatic labelling of topic models learned from Twitter by summarisation

Cite this