Location mention detection in tweets and microblogs

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Abstract

The automatic identification of location expressions in social media text is an actively researched task. We present a novel approach to detection mentions of locations in the texts of microblogs and social media. We propose an approach based on Noun Phrase extraction and n-gram based matching instead of the traditional methods using Named Entity Recognition (NER) or Conditional Random Fields (CRF), arguing that our method is better suited to noisy microblog text. Our proposed system is comprised of several individual modules to detect addresses, Points of Interest (e.g. hospitals or universities), distance and direction markers; and location names (e.g. suburbs or countries). Our system won the ALTA 2014 Twitter Location Detection shared task with an F-score of 0.792 for detecting location expressions in a test set of 1,000 tweets, demonstrating its efficacy for this task. A number of directions for future work are discussed.

LanguageEnglish
Title of host publicationComputational Linguistics - 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Revised Selected Papers
EditorsKôiti Hasida, Ayu Purwarianti
Place of PublicationSingapore
PublisherSpringer, Springer Nature
Pages123-134
Number of pages12
Volume593
ISBN (Print)9789811005145
DOIs
Publication statusPublished - 2016
Event14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015 - Bali, Indonesia
Duration: 19 May 201521 May 2015

Publication series

NameCommunications in Computer and Information Science
Volume593
ISSN (Print)1865-0929

Other

Other14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015
CountryIndonesia
CityBali
Period19/05/1521/05/15

Cite this

Malmasi, S., & Dras, M. (2016). Location mention detection in tweets and microblogs. In K. Hasida, & A. Purwarianti (Eds.), Computational Linguistics - 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Revised Selected Papers (Vol. 593, pp. 123-134). (Communications in Computer and Information Science; Vol. 593). Singapore: Springer, Springer Nature. https://doi.org/10.1007/978-981-10-0515-2_9
Malmasi, Shervin ; Dras, Mark. / Location mention detection in tweets and microblogs. Computational Linguistics - 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Revised Selected Papers. editor / Kôiti Hasida ; Ayu Purwarianti. Vol. 593 Singapore : Springer, Springer Nature, 2016. pp. 123-134 (Communications in Computer and Information Science).
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title = "Location mention detection in tweets and microblogs",
abstract = "The automatic identification of location expressions in social media text is an actively researched task. We present a novel approach to detection mentions of locations in the texts of microblogs and social media. We propose an approach based on Noun Phrase extraction and n-gram based matching instead of the traditional methods using Named Entity Recognition (NER) or Conditional Random Fields (CRF), arguing that our method is better suited to noisy microblog text. Our proposed system is comprised of several individual modules to detect addresses, Points of Interest (e.g. hospitals or universities), distance and direction markers; and location names (e.g. suburbs or countries). Our system won the ALTA 2014 Twitter Location Detection shared task with an F-score of 0.792 for detecting location expressions in a test set of 1,000 tweets, demonstrating its efficacy for this task. A number of directions for future work are discussed.",
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Malmasi, S & Dras, M 2016, Location mention detection in tweets and microblogs. in K Hasida & A Purwarianti (eds), Computational Linguistics - 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Revised Selected Papers. vol. 593, Communications in Computer and Information Science, vol. 593, Springer, Springer Nature, Singapore, pp. 123-134, 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Bali, Indonesia, 19/05/15. https://doi.org/10.1007/978-981-10-0515-2_9

Location mention detection in tweets and microblogs. / Malmasi, Shervin; Dras, Mark.

Computational Linguistics - 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Revised Selected Papers. ed. / Kôiti Hasida; Ayu Purwarianti. Vol. 593 Singapore : Springer, Springer Nature, 2016. p. 123-134 (Communications in Computer and Information Science; Vol. 593).

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

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AB - The automatic identification of location expressions in social media text is an actively researched task. We present a novel approach to detection mentions of locations in the texts of microblogs and social media. We propose an approach based on Noun Phrase extraction and n-gram based matching instead of the traditional methods using Named Entity Recognition (NER) or Conditional Random Fields (CRF), arguing that our method is better suited to noisy microblog text. Our proposed system is comprised of several individual modules to detect addresses, Points of Interest (e.g. hospitals or universities), distance and direction markers; and location names (e.g. suburbs or countries). Our system won the ALTA 2014 Twitter Location Detection shared task with an F-score of 0.792 for detecting location expressions in a test set of 1,000 tweets, demonstrating its efficacy for this task. A number of directions for future work are discussed.

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Malmasi S, Dras M. Location mention detection in tweets and microblogs. In Hasida K, Purwarianti A, editors, Computational Linguistics - 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Revised Selected Papers. Vol. 593. Singapore: Springer, Springer Nature. 2016. p. 123-134. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-10-0515-2_9