research-article

Small-Scale Incident Detection based on Microposts

Authors:

Benedikt Schmidt,

Thorsten StrufeAuthors Info & Claims

HT '15: Proceedings of the 26th ACM Conference on Hypertext & Social Media

Pages 3 - 12

https://doi.org/10.1145/2700171.2791038

Published: 24 August 2015 Publication History

Abstract

Detecting large-scale incidents based on microposts has successfully been proposed and shown. However, the detection of small-scale incidents was not satisfyingly possible so far, though the information that is shared during such local events could improve the situational awareness of both citizens and decision makers alike.

In this paper, we propose an approach for small-scale incident detection based on spatial-temporal-type clustering. In contrast to existing work, (1) we employ three distinct properties that define an incident, (2) we use a hybrid approach to reduce the computational overhead, and (3) we extract generalized features to increase robustness towards previously unseen data. Our evaluation in the domain of emergency first response shows that our approach identifies 32.14% of all real world incidents recorded for the city of Seattle just using on tweets. This result greatly outperforms the state of the art, which only detects about 6% of the real-world incidents. Also, a precision of 77% shows that we efficiently discard irrelevant information.

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Cited By

Das SWei ZDutta A(2022)Rules mining on hybrid electric vehicle consumer complaint databaseJournal of Transportation Safety & Security10.1080/19439962.2022.214761415:10(987-1007)Online publication date: 24-Nov-2022
https://doi.org/10.1080/19439962.2022.2147614
Sun DYang CLi JWang RYao SShao HLiu DLiu SWang TAbdelzaher T(2021)Computational Modeling of Hierarchically Polarized Groups by Structured Matrix FactorizationFrontiers in Big Data10.3389/fdata.2021.7298814Online publication date: 22-Dec-2021
https://doi.org/10.3389/fdata.2021.729881
Yang CLi JWang RYao SShao HLiu DLiu SWang TAbdelzaher TAlhajj R(2020)Hierarchical overlapping belief estimation by structured matrix factorizationProceedings of the 12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1109/ASONAM49781.2020.9381477(81-88)Online publication date: 7-Dec-2020
https://dl.acm.org/doi/10.1109/ASONAM49781.2020.9381477
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Index Terms

Small-Scale Incident Detection based on Microposts
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
  2. Information systems applications
    1. Data mining
      1. Clustering

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Published In

cover image ACM Conferences

HT '15: Proceedings of the 26th ACM Conference on Hypertext & Social Media

August 2015

360 pages

ISBN:9781450333955

DOI:10.1145/2700171

General Chair:
Yeliz Yesilada
Middle East Technical University Northern Cyprus Campus
,
Program Chairs:
Rosta Farzan
University of Pittsburgh, USA
,
Geert-Jan Houben
Delft University of Technology, The Netherlands

Copyright © 2015 ACM.

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 the author(s) 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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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

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Published: 24 August 2015

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HT '15: 26th ACM Conference on Hypertext and Social Media

September 1 - 4, 2015

Guzelyurt, Northern Cyprus

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HT '15 Paper Acceptance Rate 24 of 60 submissions, 40%;

Overall Acceptance Rate 378 of 1,158 submissions, 33%

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Cited By

Das SWei ZDutta A(2022)Rules mining on hybrid electric vehicle consumer complaint databaseJournal of Transportation Safety & Security10.1080/19439962.2022.214761415:10(987-1007)Online publication date: 24-Nov-2022
https://doi.org/10.1080/19439962.2022.2147614
Sun DYang CLi JWang RYao SShao HLiu DLiu SWang TAbdelzaher T(2021)Computational Modeling of Hierarchically Polarized Groups by Structured Matrix FactorizationFrontiers in Big Data10.3389/fdata.2021.7298814Online publication date: 22-Dec-2021
https://doi.org/10.3389/fdata.2021.729881
Yang CLi JWang RYao SShao HLiu DLiu SWang TAbdelzaher TAlhajj R(2020)Hierarchical overlapping belief estimation by structured matrix factorizationProceedings of the 12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1109/ASONAM49781.2020.9381477(81-88)Online publication date: 7-Dec-2020
https://dl.acm.org/doi/10.1109/ASONAM49781.2020.9381477
Yu ZWu XXie XXu J(2019)Hot Event Detection for Social Media Based on Keyword Semantic Information2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC)10.1109/DSC.2019.00068(410-415)Online publication date: Jun-2019
https://doi.org/10.1109/DSC.2019.00068
Abulaish MSharma SFazil M(2019)A Multi-Attributed Graph-Based Approach for Text Data Modeling and Event Detection in Twitter2019 11th International Conference on Communication Systems & Networks (COMSNETS)10.1109/COMSNETS.2019.8711451(703-708)Online publication date: Jan-2019
https://doi.org/10.1109/COMSNETS.2019.8711451
Ahmed MVanajakshi LSuriyanarayanan R(2019)Real-Time Traffic Congestion Information from Tweets Using Supervised and Unsupervised Machine Learning TechniquesTransportation in Developing Economies10.1007/s40890-019-0088-25:2Online publication date: 4-Oct-2019
https://doi.org/10.1007/s40890-019-0088-2
Mousset PPitarch YTamine LLee DSastry NWeber I(2018)Studying the Spatio-Temporal Dynamics of Small-Scale Events in TwitterProceedings of the 29th on Hypertext and Social Media10.1145/3209542.3209561(73-81)Online publication date: 3-Jul-2018
https://dl.acm.org/doi/10.1145/3209542.3209561
Wu YChen ZSun GXie XCao NLiu SCui W(2018)StreamExplorerIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2017.276445924:10(2758-2772)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1109/TVCG.2017.2764459
Nagaki SKitagawa H(2017)Recency-based candidate selection for efficient entity linkingProceedings of the 19th International Conference on Information Integration and Web-based Applications & Services10.1145/3151759.3151771(405-414)Online publication date: 4-Dec-2017
https://dl.acm.org/doi/10.1145/3151759.3151771
Mallela DAhlers DPera MSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)Mining Twitter features for event summarization and ratingProceedings of the International Conference on Web Intelligence10.1145/3106426.3106487(615-622)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106487
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