research-article

Mining the web to predict future events

Authors:

Eric HorvitzAuthors Info & Claims

WSDM '13: Proceedings of the sixth ACM international conference on Web search and data mining

Pages 255 - 264

https://doi.org/10.1145/2433396.2433431

Published: 04 February 2013 Publication History

Abstract

We describe and evaluate methods for learning to forecast forthcoming events of interest from a corpus containing 22 years of news stories. We consider the examples of identifying significant increases in the likelihood of disease outbreaks, deaths, and riots in advance of the occurrence of these events in the world. We provide details of methods and studies, including the automated extraction and generalization of sequences of events from news corpora and multiple web resources. We evaluate the predictive power of the approach on real-world events withheld from the system.

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Cited By

Deng Sde Rijke MNing YBaeza-Yates RBonchi F(2024)Advances in Human Event Modeling: From Graph Neural Networks to Language ModelsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671466(6459-6469)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671466
Regev JJatowt AFärber MAngélica LLattanzi SMuñoz Medina AAkoglu LGionis AVassilvitskii S(2024)Future Timelines: Extraction and Visualization of Future-related Content From News ArticlesProceedings of the 17th ACM International Conference on Web Search and Data Mining10.1145/3616855.3635693(1082-1085)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1145/3616855.3635693
Singh PJain A(2024)Context-Aware Civil Unrest Event Prediction Using Neutrosophic-Aspect-Based Sentiment Analysis, PSO, and Hierarchical LSTMIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.333850911:3(3667-3677)Online publication date: Jun-2024
https://doi.org/10.1109/TCSS.2023.3338509
Show More Cited By

Index Terms

Mining the web to predict future events
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
  2. Machine learning
    1. Learning settings
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Natural language interfaces

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Published In

cover image ACM Conferences

WSDM '13: Proceedings of the sixth ACM international conference on Web search and data mining

February 2013

816 pages

ISBN:9781450318693

DOI:10.1145/2433396

General Chairs:
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy
,
Program Chairs:
Paolo Ferragina
University of Pisa, Italy
,
Aristides Gionis
Yahoo! Research, Barcelona, Spain

Copyright © 2013 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 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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Published: 04 February 2013

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WSDM 2013

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WSDM 2013: Sixth ACM International Conference on Web Search and Data Mining

February 4 - 8, 2013

Rome, Italy

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Overall Acceptance Rate 498 of 2,863 submissions, 17%

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Cited By

Deng Sde Rijke MNing YBaeza-Yates RBonchi F(2024)Advances in Human Event Modeling: From Graph Neural Networks to Language ModelsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671466(6459-6469)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671466
Regev JJatowt AFärber MAngélica LLattanzi SMuñoz Medina AAkoglu LGionis AVassilvitskii S(2024)Future Timelines: Extraction and Visualization of Future-related Content From News ArticlesProceedings of the 17th ACM International Conference on Web Search and Data Mining10.1145/3616855.3635693(1082-1085)Online publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1145/3616855.3635693
Singh PJain A(2024)Context-Aware Civil Unrest Event Prediction Using Neutrosophic-Aspect-Based Sentiment Analysis, PSO, and Hierarchical LSTMIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.333850911:3(3667-3677)Online publication date: Jun-2024
https://doi.org/10.1109/TCSS.2023.3338509
Ihsan RKhurshid SShoaib MAli SMahnoor SHamza S(2024)A technique to forecast Pakistan’s news using deep hybrid learning modelInternational Journal of Information Technology10.1007/s41870-024-01781-616:4(2505-2516)Online publication date: 11-Mar-2024
https://doi.org/10.1007/s41870-024-01781-6
Zhang YTang X(2023)News event prediction by trigger evolution graph and event segmentJournal of Systems Engineering and Electronics10.23919/JSEE.2023.00008334:3(615-626)Online publication date: Jun-2023
https://doi.org/10.23919/JSEE.2023.000083
Jiao YZhong MShen JZhang YZhang CHan J(2023)Unsupervised Event Chain Mining from Multiple DocumentsProceedings of the ACM Web Conference 202310.1145/3543507.3583295(1948-1959)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1145/3543507.3583295
Xudong HJun WJun H(2023)Cross-lingual Related Events Recognition Methods Based on The Event Central News Sets2023 38th Youth Academic Annual Conference of Chinese Association of Automation (YAC)10.1109/YAC59482.2023.10401576(539-545)Online publication date: 27-Aug-2023
https://doi.org/10.1109/YAC59482.2023.10401576
Tan FZuo XNg S(2023)UniCausal: Unified Benchmark and Repository for Causal Text MiningBig Data Analytics and Knowledge Discovery10.1007/978-3-031-39831-5_23(248-262)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1007/978-3-031-39831-5_23
Matsumaru KIkejiri RSumikawa Y(2023)Present Causal Relationship Retrieval for Historical AnalogyCulture and Computing10.1007/978-3-031-34732-0_41(536-547)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-34732-0_41
Hossain KHarutyunyan HNing YKennedy BRamakrishnan NGalstyan A(2022)Identifying geopolitical event precursors using attention-based LSTMsFrontiers in Artificial Intelligence10.3389/frai.2022.8938755Online publication date: 31-Oct-2022
https://doi.org/10.3389/frai.2022.893875
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