research-article

Tweet trend analysis in an emergency situation

Authors:

Takeshi Sakaki,

Fujio Toriumi,

Yutaka MatsuoAuthors Info & Claims

SWID '11: Proceedings of the Special Workshop on Internet and Disasters

Article No.: 3, Pages 1 - 8

https://doi.org/10.1145/2079360.2079363

Published: 06 December 2011 Publication History

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Abstract

The Great Eastern Japan Earthquake, which struck Japan on March 11, catastrophically affected all aspects of life: buildings, power plants, human life, etc. Moreover, it caused severe problems related to network infrastructure. We can ascertain the degree of network disorder from network traffic logs. Although we can infer what people did when the earthquake occurred on the Web from network traffic logs, we cannot know it precisely. Social media were used effectively during and after this earthquake, and they left a partial log revealing what people did on the Web during and after the earthquake. Such a log is one of the first logs of people's actions in a time of a catastrophic disaster. As described in this paper, we analyze Twitter logs and attempt to extract what happened in the emergency situation.

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Rai DChhikara G(2023)Tweet Analysis: What changed over time?2023 International Conference on Advanced Computing Technologies and Applications (ICACTA)10.1109/ICACTA58201.2023.10392313(1-7)Online publication date: 6-Oct-2023
https://doi.org/10.1109/ICACTA58201.2023.10392313
Williams WCeci S(2023)How Politically Motivated Social Media and Lack of Political Diversity Corrupt ScienceIdeological and Political Bias in Psychology10.1007/978-3-031-29148-7_13(357-375)Online publication date: 14-Sep-2023
https://doi.org/10.1007/978-3-031-29148-7_13
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SWID '11: Proceedings of the Special Workshop on Internet and Disasters

December 2011

74 pages

ISBN:9781450310444

DOI:10.1145/2079360

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 06 December 2011

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Co-NEXT '11

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SIGCOMM

Co-NEXT '11: Conference on emerging Networking Experiments and Technologies

December 6 - 9, 2011

Tokyo, Japan

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Rai DChhikara G(2023)Tweet Analysis: What changed over time?2023 International Conference on Advanced Computing Technologies and Applications (ICACTA)10.1109/ICACTA58201.2023.10392313(1-7)Online publication date: 6-Oct-2023
https://doi.org/10.1109/ICACTA58201.2023.10392313
Williams WCeci S(2023)How Politically Motivated Social Media and Lack of Political Diversity Corrupt ScienceIdeological and Political Bias in Psychology10.1007/978-3-031-29148-7_13(357-375)Online publication date: 14-Sep-2023
https://doi.org/10.1007/978-3-031-29148-7_13
Mondal SSahoo JWang JMondal KRahman M(2022)Fake News Detection Exploiting TF-IDF Vectorization with Ensemble Learning ModelsAdvances in Distributed Computing and Machine Learning10.1007/978-981-16-4807-6_25(261-270)Online publication date: 1-Jan-2022
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Kumar DUkkusuri SChampin PGandon FMédini LLalmas MIpeirotis P(2018)Utilizing Geo-tagged Tweets to Understand Evacuation Dynamics during EmergenciesCompanion Proceedings of the The Web Conference 201810.1145/3184558.3191619(1613-1620)Online publication date: 23-Apr-2018
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Emergency situation awareness from twitter for crisis management

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