Survey on social event detection

Yutao Huang; Qing Liao; Yan Jia; Ye Wang

doi:10.1109/DSC53577.2021.00029

Survey on social event detection

Yutao Huang
, Qing Liao
, Yan Jia
, Ye Wang^*

^*Corresponding author for this work

Harbin Institute of Technology

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

1 Scopus citations

Abstract

In this society, the way people obtain information has gradually shifted from traditional media to social media applications. Social media applications publish a large number of real-world events every day. With more and more information about events in social networks, more and more information is contained. Social event detection refers to extracting interrelated message clusters from a social media message corpus or social message stream to represent specific events in the real world. Combining social event detection with different domain knowledge can research and mine different information. In this article, we will explore social event detection based on topic models, community discovery, and heterogeneous information networks.

Original language	English
Title of host publication	Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	159-165
Number of pages	7
ISBN (Electronic)	9781665418157
DOIs	https://doi.org/10.1109/DSC53577.2021.00029
State	Published - 2021
Externally published	Yes
Event	6th IEEE International Conference on Data Science in Cyberspace, DSC 2021 - ShenZhen, China Duration: 9 Oct 2021 → 11 Oct 2021

Publication series

Name	Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021

Conference

Conference	6th IEEE International Conference on Data Science in Cyberspace, DSC 2021
Country/Territory	China
City	ShenZhen
Period	9/10/21 → 11/10/21

Keywords

community discovery
heterogeneous information networks
social event detection
social networks
topic models

Access to Document

10.1109/DSC53577.2021.00029

Cite this

Huang, Y., Liao, Q., Jia, Y., & Wang, Y. (2021). Survey on social event detection. In Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021 (pp. 159-165). (Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DSC53577.2021.00029

@inproceedings{89798eb259734a2e9ac9da5ee86e18a2,

title = "Survey on social event detection",

abstract = "In this society, the way people obtain information has gradually shifted from traditional media to social media applications. Social media applications publish a large number of real-world events every day. With more and more information about events in social networks, more and more information is contained. Social event detection refers to extracting interrelated message clusters from a social media message corpus or social message stream to represent specific events in the real world. Combining social event detection with different domain knowledge can research and mine different information. In this article, we will explore social event detection based on topic models, community discovery, and heterogeneous information networks.",

keywords = "community discovery, heterogeneous information networks, social event detection, social networks, topic models",

author = "Yutao Huang and Qing Liao and Yan Jia and Ye Wang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 6th IEEE International Conference on Data Science in Cyberspace, DSC 2021 ; Conference date: 09-10-2021 Through 11-10-2021",

year = "2021",

doi = "10.1109/DSC53577.2021.00029",

language = "英语",

series = "Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021",

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

pages = "159--165",

booktitle = "Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021",

address = "美国",

}

Huang, Y, Liao, Q, Jia, Y & Wang, Y 2021, Survey on social event detection. in Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021. Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 159-165, 6th IEEE International Conference on Data Science in Cyberspace, DSC 2021, ShenZhen, China, 9/10/21. https://doi.org/10.1109/DSC53577.2021.00029

Survey on social event detection. / Huang, Yutao; Liao, Qing; Jia, Yan et al.
Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 159-165 (Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021).

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

TY - GEN

T1 - Survey on social event detection

AU - Huang, Yutao

AU - Liao, Qing

AU - Jia, Yan

AU - Wang, Ye

PY - 2021

Y1 - 2021

N2 - In this society, the way people obtain information has gradually shifted from traditional media to social media applications. Social media applications publish a large number of real-world events every day. With more and more information about events in social networks, more and more information is contained. Social event detection refers to extracting interrelated message clusters from a social media message corpus or social message stream to represent specific events in the real world. Combining social event detection with different domain knowledge can research and mine different information. In this article, we will explore social event detection based on topic models, community discovery, and heterogeneous information networks.

AB - In this society, the way people obtain information has gradually shifted from traditional media to social media applications. Social media applications publish a large number of real-world events every day. With more and more information about events in social networks, more and more information is contained. Social event detection refers to extracting interrelated message clusters from a social media message corpus or social message stream to represent specific events in the real world. Combining social event detection with different domain knowledge can research and mine different information. In this article, we will explore social event detection based on topic models, community discovery, and heterogeneous information networks.

KW - community discovery

KW - heterogeneous information networks

KW - social event detection

KW - social networks

KW - topic models

UR - https://www.scopus.com/pages/publications/85128758959

U2 - 10.1109/DSC53577.2021.00029

DO - 10.1109/DSC53577.2021.00029

M3 - 会议稿件

AN - SCOPUS:85128758959

T3 - Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021

SP - 159

EP - 165

BT - Proceedings - 2021 IEEE 6th International Conference on Data Science in Cyberspace, DSC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th IEEE International Conference on Data Science in Cyberspace, DSC 2021

Y2 - 9 October 2021 through 11 October 2021

ER -

Survey on social event detection

Abstract

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Conference

Keywords

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