EQSA: Earthquake Situational Analytics from Social Media

Huyen N. Nguyen; Tommy Dang

doi:10.1109/VAST47406.2019.8986947

EQSA: Earthquake Situational Analytics from Social Media

Huyen N. Nguyen, Tommy Dang

Computer Science

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

2 Scopus citations

Abstract

This paper introduces EQSA, an interactive exploratory tool for earthquake situational analytics using social media. EQSA is designed to support users to characterize the condition across the area around the earthquake zone, regarding related events, resources to be allocated, and responses from the community. On the general level, changes in the volume of messages from chosen categories are presented, assisting users in conveying a general idea of the condition. More in-depth analysis is provided with topic evolution, community visualization, and location representation. EQSA is developed with intuitive, interactive features and multiple linked views, visualizing social media data, and supporting users to gain a comprehensive insight into the situation. In this paper, we present the application of EQSA with the VAST Challenge 2019: Mini-Challenge 3 (MC3) dataset.

Original language	English
Title of host publication	2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings
Editors	Remco Chang, Daniel Keim, Ross Maciejewski
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	142-143
Number of pages	2
ISBN (Electronic)	9781728122847
DOIs	https://doi.org/10.1109/VAST47406.2019.8986947
State	Published - Oct 2019
Event	14th IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Vancouver, Canada Duration: Oct 20 2019 → Oct 25 2019

Publication series

Name	2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings

Conference

Conference	14th IEEE Conference on Visual Analytics Science and Technology, VAST 2019
Country	Canada
City	Vancouver
Period	10/20/19 → 10/25/19

Keywords

EQSA
Earthquake Analysis
Interactive Visualization
Mini-Challenge 3
Social Media Data
VAST Challenge 2019
Visual Analytics
WordStream

Access to Document

10.1109/VAST47406.2019.8986947

Link to publication in Scopus

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Cite this

Nguyen, H. N., & Dang, T. (2019). EQSA: Earthquake Situational Analytics from Social Media. In R. Chang, D. Keim, & R. Maciejewski (Eds.), 2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings (pp. 142-143). [8986947] (2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VAST47406.2019.8986947

Nguyen, Huyen N. ; Dang, Tommy. / EQSA : Earthquake Situational Analytics from Social Media. 2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings. editor / Remco Chang ; Daniel Keim ; Ross Maciejewski. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 142-143 (2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings).

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abstract = "This paper introduces EQSA, an interactive exploratory tool for earthquake situational analytics using social media. EQSA is designed to support users to characterize the condition across the area around the earthquake zone, regarding related events, resources to be allocated, and responses from the community. On the general level, changes in the volume of messages from chosen categories are presented, assisting users in conveying a general idea of the condition. More in-depth analysis is provided with topic evolution, community visualization, and location representation. EQSA is developed with intuitive, interactive features and multiple linked views, visualizing social media data, and supporting users to gain a comprehensive insight into the situation. In this paper, we present the application of EQSA with the VAST Challenge 2019: Mini-Challenge 3 (MC3) dataset.",

keywords = "EQSA, Earthquake Analysis, Interactive Visualization, Mini-Challenge 3, Social Media Data, VAST Challenge 2019, Visual Analytics, WordStream",

author = "Nguyen, {Huyen N.} and Tommy Dang",

year = "2019",

month = oct,

doi = "10.1109/VAST47406.2019.8986947",

language = "English",

series = "2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "142--143",

editor = "Remco Chang and Daniel Keim and Ross Maciejewski",

booktitle = "2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings",

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Nguyen, HN & Dang, T 2019, EQSA: Earthquake Situational Analytics from Social Media. in R Chang, D Keim & R Maciejewski (eds), 2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings., 8986947, 2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 142-143, 14th IEEE Conference on Visual Analytics Science and Technology, VAST 2019, Vancouver, Canada, 10/20/19. https://doi.org/10.1109/VAST47406.2019.8986947

EQSA : Earthquake Situational Analytics from Social Media. / Nguyen, Huyen N.; Dang, Tommy.

2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings. ed. / Remco Chang; Daniel Keim; Ross Maciejewski. Institute of Electrical and Electronics Engineers Inc., 2019. p. 142-143 8986947 (2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings).

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

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Nguyen HN, Dang T. EQSA: Earthquake Situational Analytics from Social Media. In Chang R, Keim D, Maciejewski R, editors, 2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 142-143. 8986947. (2019 IEEE Conference on Visual Analytics Science and Technology, VAST 2019 - Proceedings). https://doi.org/10.1109/VAST47406.2019.8986947