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Detecting controversial events from twitter

Authors:

Ana-Maria Popescu,

Marco PennacchiottiAuthors Info & Claims

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

Pages 1873 - 1876

https://doi.org/10.1145/1871437.1871751

Published: 26 October 2010 Publication History

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Abstract

Social media provides researchers with continuously updated information about developments of interest to large audiences. This paper addresses the task of identifying controversial events using Twitter as a starting point: we propose 3 models for this task and report encouraging initial results.

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Cited By

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Xu TChen AZhao YGao JGan TCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)A Chinese Multimodal Social Video Dataset for Controversy DetectionProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681630(2898-2907)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681630
Yang ZYang ZGuo ZLin ZZhu HLi QLiu W(2024)Towards Temporal Event Detection: A Dataset, Benchmarks and ChallengesIEEE Transactions on Multimedia10.1109/TMM.2023.327652326(1102-1113)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2023.3276523
Lin ZXie JLi Q(2024)Multi-modal news event detection with external knowledgeInformation Processing & Management10.1016/j.ipm.2024.10369761:3(103697)Online publication date: May-2024
https://doi.org/10.1016/j.ipm.2024.103697
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Index Terms

Detecting controversial events from twitter
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Information & Contributors

Information

Published In

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

October 2010

2036 pages

ISBN:9781450300995

DOI:10.1145/1871437

General Chair:
Jimmy Huang
York University, Canada
,
Program Chairs:
Nick Koudas
University of Toronto, Canada
,
Gareth Jones
Dublin City University, Ireland
,
Xindong Wu
University of Vermont, USA
,
Kevyn Collins-Thompson
Microsoft Research, USA
,
Aijun An
York University, Canada

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

Publication History

Published: 26 October 2010

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CIKM '10

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CIKM '10: International Conference on Information and Knowledge Management

October 26 - 30, 2010

ON, Toronto, Canada

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

View all

Xu TChen AZhao YGao JGan TCai JKankanhalli MPrabhakaran BBoll SSubramanian RZheng LSingh VCesar PXie LXu D(2024)A Chinese Multimodal Social Video Dataset for Controversy DetectionProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681630(2898-2907)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3664647.3681630
Yang ZYang ZGuo ZLin ZZhu HLi QLiu W(2024)Towards Temporal Event Detection: A Dataset, Benchmarks and ChallengesIEEE Transactions on Multimedia10.1109/TMM.2023.327652326(1102-1113)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2023.3276523
Lin ZXie JLi Q(2024)Multi-modal news event detection with external knowledgeInformation Processing & Management10.1016/j.ipm.2024.10369761:3(103697)Online publication date: May-2024
https://doi.org/10.1016/j.ipm.2024.103697
de França Fdi Genova DPenteado CKamienski C(2023)Understanding conflict origin and dynamics on Twitter: A real-time detection systemExpert Systems with Applications10.1016/j.eswa.2022.118748212(118748)Online publication date: Feb-2023
https://doi.org/10.1016/j.eswa.2022.118748
Badache IChifu AFournier S(2022)Unsupervised and Supervised Methods to Estimate Temporal-Aware Contradictions in Online Course ReviewsMathematics10.3390/math1005080910:5(809)Online publication date: 3-Mar-2022
https://doi.org/10.3390/math10050809
Ariestya AParamitha GElmada M(2022)Climate change awareness of gen z: the influence of frame and jargon on online newsJurnal Studi Komunikasi (Indonesian Journal of Communications Studies)10.25139/jsk.v6i3.52876:3(753-770)Online publication date: 10-Nov-2022
https://doi.org/10.25139/jsk.v6i3.5287
Pradhan AMohanty HLal R(2022)Events in Tweets: Graph-Based TechniquesRecent Advances in Computer Science and Communications10.2174/266625581399920090413375915:2(155-169)Online publication date: Feb-2022
https://doi.org/10.2174/2666255813999200904133759
Li LWan YPlewczynski DZhi M(2022)Simulation Model on Network Public Opinion Communication Model of Major Public Health Emergency and Management System DesignScientific Programming10.1155/2022/59024452022Online publication date: 1-Jan-2022
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Li QChao YLi DLu YZhang C(2022)Event Detection from Social Media Stream: Methods, Datasets and Opportunities2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020411(3509-3516)Online publication date: 17-Dec-2022
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Senaratne HLehle DSchreck T(2022)Characteristics Analysis of Moving Conversations to Detect Events on Twitter2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)10.1109/ASONAM55673.2022.10068690(476-483)Online publication date: 10-Nov-2022
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