@inproceedings{ab0bb79f32264603b650b5fe5221078e,
title = "EQSA: Earthquake Situational Analytics from Social Media",
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",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; null ; Conference date: 20-10-2019 Through 25-10-2019",
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",
}