Dynamic-keyword extraction from social media

David Semedo; João Magalhães

doi:10.1007/978-3-030-15712-8_62

Dynamic-keyword extraction from social media

David Semedo, João Magalhães

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Traditional keyword extraction methods make the assumption that corpora is static. However, in social media, information is highly dynamic, with individual words showing a dynamic behaviour. In this paper we propose an unsupervised approach that jointly models words’ temporal behaviour and keyword’s semantic affinity, to address the task of dynamic-keyword extraction. Experiments show the method effectiveness and confirm the importance of exploiting keyword dynamics.

Original language	English
Title of host publication	Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings
Editors	Norbert Fuhr, Leif Azzopardi, Benno Stein, Claudia Hauff, Philipp Mayr, Djoerd Hiemstra
Place of Publication	Cham
Publisher	Springer
Pages	852-860
Number of pages	9
ISBN (Electronic)	978-3-030-15712-8
ISBN (Print)	978-3-030-15711-1
DOIs	https://doi.org/10.1007/978-3-030-15712-8_62
Publication status	Published - 1 Jan 2019
Event	41st European Conference on Information Retrieval, ECIR 2019 - Cologne, Germany Duration: 14 Apr 2019 → 18 Apr 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer
Volume	11437 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	41st European Conference on Information Retrieval, ECIR 2019
Country/Territory	Germany
City	Cologne
Period	14/04/19 → 18/04/19

Keywords

Dynamic keyword extraction
Information extraction
Social media

Access to Document

10.1007/978-3-030-15712-8_62

Cite this

Semedo, D., & Magalhães, J. (2019). Dynamic-keyword extraction from social media. In N. Fuhr, L. Azzopardi, B. Stein, C. Hauff, P. Mayr, & D. Hiemstra (Eds.), Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings (pp. 852-860). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11437 LNCS). Springer. https://doi.org/10.1007/978-3-030-15712-8_62

Semedo, David ; Magalhães, João. / Dynamic-keyword extraction from social media. Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. editor / Norbert Fuhr ; Leif Azzopardi ; Benno Stein ; Claudia Hauff ; Philipp Mayr ; Djoerd Hiemstra. Cham : Springer, 2019. pp. 852-860 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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keywords = "Dynamic keyword extraction, Information extraction, Social media",

author = "David Semedo and Jo{\~a}o Magalh{\~a}es",

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Semedo, D & Magalhães, J 2019, Dynamic-keyword extraction from social media. in N Fuhr, L Azzopardi, B Stein, C Hauff, P Mayr & D Hiemstra (eds), Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11437 LNCS, Springer, Cham, pp. 852-860, 41st European Conference on Information Retrieval, ECIR 2019, Cologne, Germany, 14/04/19. https://doi.org/10.1007/978-3-030-15712-8_62

Dynamic-keyword extraction from social media. / Semedo, David ; Magalhães, João.
Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. ed. / Norbert Fuhr; Leif Azzopardi; Benno Stein; Claudia Hauff; Philipp Mayr; Djoerd Hiemstra. Cham: Springer, 2019. p. 852-860 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11437 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Traditional keyword extraction methods make the assumption that corpora is static. However, in social media, information is highly dynamic, with individual words showing a dynamic behaviour. In this paper we propose an unsupervised approach that jointly models words’ temporal behaviour and keyword’s semantic affinity, to address the task of dynamic-keyword extraction. Experiments show the method effectiveness and confirm the importance of exploiting keyword dynamics.

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Semedo D , Magalhães J. Dynamic-keyword extraction from social media. In Fuhr N, Azzopardi L, Stein B, Hauff C, Mayr P, Hiemstra D, editors, Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings. Cham: Springer. 2019. p. 852-860. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-15712-8_62

Dynamic-keyword extraction from social media

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