Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection

Daniel Preoţiuc-Pietro; P. K. Srijith; Mark Hepple; Trevor Cohn

Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection

Daniel Preoţiuc-Pietro, P. K. Srijith, Mark Hepple, Trevor Cohn

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Abstract

Streaming media provides a number of unique challenges for computational linguistics. This paper studies the temporal variation in word co-occurrence statistics, with application to event detection. We develop a spectral clustering approach to find groups of mutually informative terms occurring in discrete time frames. Experiments on large datasets of tweets show that these groups identify key real world events as they occur in time, despite no explicit supervision. The performance of our method rivals state-of-the-art methods for event detection on F-score, obtaining higher recall at the expense of precision.

Anthology ID:: L16-1694
Volume:: Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:: May
Year:: 2016
Address:: Portorož, Slovenia
Editors:: Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:: LREC
SIG:
Publisher:: European Language Resources Association (ELRA)
Note:
Pages:: 4380–4387
Language:
URL:: https://aclanthology.org/L16-1694/
DOI:
Bibkey:
Cite (ACL):: Daniel Preoţiuc-Pietro, P. K. Srijith, Mark Hepple, and Trevor Cohn. 2016. Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 4380–4387, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):: Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection (Preoţiuc-Pietro et al., LREC 2016)
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PDF:: https://aclanthology.org/L16-1694.pdf

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@inproceedings{preotiuc-pietro-etal-2016-studying,
    title = "Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection",
    author = "Preo{\c{t}}iuc-Pietro, Daniel  and
      Srijith, P. K.  and
      Hepple, Mark  and
      Cohn, Trevor",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Grobelnik, Marko  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, Helene  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
    month = may,
    year = "2016",
    address = "Portoro{\v{z}}, Slovenia",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://aclanthology.org/L16-1694/",
    pages = "4380--4387",
    abstract = "Streaming media provides a number of unique challenges for computational linguistics. This paper studies the temporal variation in word co-occurrence statistics, with application to event detection. We develop a spectral clustering approach to find groups of mutually informative terms occurring in discrete time frames. Experiments on large datasets of tweets show that these groups identify key real world events as they occur in time, despite no explicit supervision. The performance of our method rivals state-of-the-art methods for event detection on F-score, obtaining higher recall at the expense of precision."
}

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%0 Conference Proceedings
%T Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection
%A Preoţiuc-Pietro, Daniel
%A Srijith, P. K.
%A Hepple, Mark
%A Cohn, Trevor
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F preotiuc-pietro-etal-2016-studying
%X Streaming media provides a number of unique challenges for computational linguistics. This paper studies the temporal variation in word co-occurrence statistics, with application to event detection. We develop a spectral clustering approach to find groups of mutually informative terms occurring in discrete time frames. Experiments on large datasets of tweets show that these groups identify key real world events as they occur in time, despite no explicit supervision. The performance of our method rivals state-of-the-art methods for event detection on F-score, obtaining higher recall at the expense of precision.
%U https://aclanthology.org/L16-1694/
%P 4380-4387

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Markdown (Informal)

[Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection](https://aclanthology.org/L16-1694/) (Preoţiuc-Pietro et al., LREC 2016)

Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection (Preoţiuc-Pietro et al., LREC 2016)

ACL

Daniel Preoţiuc-Pietro, P. K. Srijith, Mark Hepple, and Trevor Cohn. 2016. Studying the Temporal Dynamics of Word Co-occurrences: An Application to Event Detection. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 4380–4387, Portorož, Slovenia. European Language Resources Association (ELRA).