Estimating Deflation Representing People Spreading in Stream Data
Authors: 
Takuma Toyoshima, Masaki Endo, Takuo Kikuchi, Shigeyoshi Ohno, Hiroshi IshikawaAuthors Info & Claims
Pages 111 - 116
Abstract
With the expanded use of social media such as Twitter in recent years, it has become easy to add various information such as location data using mobile devices. Using those data, one can observe the real world without using physical sensors. Therefore, social media have high operational value as social sensors. As described herein, we aim to support decision-making for people who intend to visit a specific place at which an event or some trouble recently occurred. After proposing a method of real-time extraction of data reflecting a burst state showing people's concentration, their inactivity, and continuous flow and dispersion, we confirm the method's effectiveness.
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Index Terms
- Estimating Deflation Representing People Spreading in Stream Data
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Information
Published In
June 2020
279 pages
ISBN:9781450375429
DOI:10.1145/3405962
- Conference Chairs:
- Richard Chbeir,
- Yannis Manolopoulos,
- Rajendra Akerkar,
- Jolanta Mizera-Pietraszko
Copyright © 2020 ACM.
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Association for Computing Machinery
New York, NY, United States
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Published: 24 August 2020
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WIMS 2020
WIMS 2020: The 10th International Conference on Web Intelligence, Mining and Semantics
June 30 - July 3, 2020
Biarritz, France
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WIMS 2020 Paper Acceptance Rate 35 of 63 submissions, 56%;
Overall Acceptance Rate 140 of 278 submissions, 50%
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