Real-time adaptive crawler for tracking unfolding events on Twitter

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

  • Asmelash Teka Hadgu
  • Sallam Abualhaija
  • Claudia Niederée

Research Organisations

External Research Organisations

  • University of Luxembourg
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Details

Original languageEnglish
Title of host publicationISCRAM 2019 - Proceedings
Subtitle of host publication16th International Conference on Information Systems for Crisis Response and Management
EditorsZeno Franco, Jose J. Gonzalez, Jose H. Canos
Pages923-931
Number of pages9
ISBN (electronic)9788409104987
Publication statusPublished - 2019
Event16th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2019 - Valencia, Spain
Duration: 19 May 201922 May 2019

Publication series

NameProceedings of the International ISCRAM Conference
Volume2019-May
ISSN (electronic)2411-3387

Abstract

When a major event such as a crisis situation occurs, people post messages on social media sites such as Twitter, in order to exchange information or to share emotions. These posts can provide useful information to raise situation awareness and support decision making, e.g., by aid organizations. In this paper, we propose a novel method for social media crawling, which exploits a Bayesian inference framework to keep track of keyword changes over time and uses a counter-stream to gauge the inclusion of noise and irrelevant information. In addition, we present a framework to evaluate real-time adaptive social search algorithms in a reproducible manner, which relies on a semi-automated approach for ground-truth construction. We show that our method outperforms previous methods for very large scale events.

Keywords

    Adaptive crawler, Crsis communication, Event tracking, Real-time adaptive search

ASJC Scopus subject areas

Cite this

Real-time adaptive crawler for tracking unfolding events on Twitter. / Hadgu, Asmelash Teka; Abualhaija, Sallam; Niederée, Claudia.
ISCRAM 2019 - Proceedings: 16th International Conference on Information Systems for Crisis Response and Management. ed. / Zeno Franco; Jose J. Gonzalez; Jose H. Canos. 2019. p. 923-931 (Proceedings of the International ISCRAM Conference; Vol. 2019-May).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Hadgu, AT, Abualhaija, S & Niederée, C 2019, Real-time adaptive crawler for tracking unfolding events on Twitter. in Z Franco, JJ Gonzalez & JH Canos (eds), ISCRAM 2019 - Proceedings: 16th International Conference on Information Systems for Crisis Response and Management. Proceedings of the International ISCRAM Conference, vol. 2019-May, pp. 923-931, 16th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2019, Valencia, Spain, 19 May 2019. <https://idl.iscram.org/files/asmelashtekahadgu/2019/1985_AsmelashTekaHadgu_etal2019.pdf>
Hadgu, A. T., Abualhaija, S., & Niederée, C. (2019). Real-time adaptive crawler for tracking unfolding events on Twitter. In Z. Franco, J. J. Gonzalez, & J. H. Canos (Eds.), ISCRAM 2019 - Proceedings: 16th International Conference on Information Systems for Crisis Response and Management (pp. 923-931). (Proceedings of the International ISCRAM Conference; Vol. 2019-May). https://idl.iscram.org/files/asmelashtekahadgu/2019/1985_AsmelashTekaHadgu_etal2019.pdf
Hadgu AT, Abualhaija S, Niederée C. Real-time adaptive crawler for tracking unfolding events on Twitter. In Franco Z, Gonzalez JJ, Canos JH, editors, ISCRAM 2019 - Proceedings: 16th International Conference on Information Systems for Crisis Response and Management. 2019. p. 923-931. (Proceedings of the International ISCRAM Conference).
Hadgu, Asmelash Teka ; Abualhaija, Sallam ; Niederée, Claudia. / Real-time adaptive crawler for tracking unfolding events on Twitter. ISCRAM 2019 - Proceedings: 16th International Conference on Information Systems for Crisis Response and Management. editor / Zeno Franco ; Jose J. Gonzalez ; Jose H. Canos. 2019. pp. 923-931 (Proceedings of the International ISCRAM Conference).
Download
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title = "Real-time adaptive crawler for tracking unfolding events on Twitter",
abstract = "When a major event such as a crisis situation occurs, people post messages on social media sites such as Twitter, in order to exchange information or to share emotions. These posts can provide useful information to raise situation awareness and support decision making, e.g., by aid organizations. In this paper, we propose a novel method for social media crawling, which exploits a Bayesian inference framework to keep track of keyword changes over time and uses a counter-stream to gauge the inclusion of noise and irrelevant information. In addition, we present a framework to evaluate real-time adaptive social search algorithms in a reproducible manner, which relies on a semi-automated approach for ground-truth construction. We show that our method outperforms previous methods for very large scale events.",
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Download

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AU - Hadgu, Asmelash Teka

AU - Abualhaija, Sallam

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