The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning. / Kraft, Angelie; Usbeck, Ricardo.
Data-driven Resilience Research 2022: Proceedings of the International Workshop on Data-driven Resilience Research 2022. ed. / Natanael Arndt; Sabine Gründer-Fahrer; Julia Holze; Michael Martin; Sebastian Tramp. Vol. 3376 Sun Site Central Europe (RWTH Aachen University), 2023. (CEUR Workshop Proceedings; Vol. 3376).

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Kraft, A & Usbeck, R 2023, The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning. in N Arndt, S Gründer-Fahrer, J Holze, M Martin & S Tramp (eds), Data-driven Resilience Research 2022: Proceedings of the International Workshop on Data-driven Resilience Research 2022. vol. 3376, CEUR Workshop Proceedings, vol. 3376, Sun Site Central Europe (RWTH Aachen University), 2022 International Workshop on Data-Driven Resilience Research - D2R2 2022, Leipzig, Saxony, Germany, 06.07.22. <https://ceur-ws.org/Vol-3376/paper01.pdf>

APA

Kraft, A., & Usbeck, R. (2023). The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning. In N. Arndt, S. Gründer-Fahrer, J. Holze, M. Martin, & S. Tramp (Eds.), Data-driven Resilience Research 2022: Proceedings of the International Workshop on Data-driven Resilience Research 2022 (Vol. 3376). (CEUR Workshop Proceedings; Vol. 3376). Sun Site Central Europe (RWTH Aachen University). https://ceur-ws.org/Vol-3376/paper01.pdf

Vancouver

Kraft A, Usbeck R. The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning. In Arndt N, Gründer-Fahrer S, Holze J, Martin M, Tramp S, editors, Data-driven Resilience Research 2022: Proceedings of the International Workshop on Data-driven Resilience Research 2022. Vol. 3376. Sun Site Central Europe (RWTH Aachen University). 2023. (CEUR Workshop Proceedings).

Bibtex

@inbook{2ccf38d2391b46d3a189053e0ae06855,
title = "The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning",
abstract = "Social media platforms provide a continuous stream of real-time news regarding crisis events on a global scale. Several machine learning methods utilize the crowd-sourced data for the automated detection of crises and the characterization of their precursors and aftermaths. Early detection and localization of crisis-related events can help save lives and economies. Yet, the applied automation methods introduce ethical risks worthy of investigation - especially given their high-stakes societal context. This work identifies and critically examines ethical risk factors of social media analyses of crisis events focusing on machine learning methods. We aim to sensitize researchers and practitioners to the ethical pitfalls and promote fairer and more reliable designs.",
keywords = "artificial intelligence, crisis informatics, ethics, machine learning, risks, social media, Informatics, Business informatics",
author = "Angelie Kraft and Ricardo Usbeck",
note = "The authors acknowledge the financial support by the Federal Ministry for Economic Affairs and Energy of Germany in the project CoyPu ?project number 01MK21007[G]). Publisher Copyright: {\textcopyright} 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).; 2022 International Workshop on Data-Driven Resilience Research - D2R2 2022 : Data Week Leipzig 2022, D2R2 2022 ; Conference date: 06-07-2022 Through 06-07-2022",
year = "2023",
language = "English",
volume = "3376",
series = "CEUR Workshop Proceedings",
publisher = "Sun Site Central Europe (RWTH Aachen University)",
editor = "Natanael Arndt and Sabine Gr{\"u}nder-Fahrer and Julia Holze and Michael Martin and Sebastian Tramp",
booktitle = "Data-driven Resilience Research 2022",
address = "Germany",
url = "https://2022.dataweek.de/d2r2-22/",

}

RIS

TY - CHAP

T1 - The Ethical Risks of Analyzing Crisis Events on Social Media with Machine Learning

AU - Kraft, Angelie

AU - Usbeck, Ricardo

N1 - Conference code: 1

PY - 2023

Y1 - 2023

N2 - Social media platforms provide a continuous stream of real-time news regarding crisis events on a global scale. Several machine learning methods utilize the crowd-sourced data for the automated detection of crises and the characterization of their precursors and aftermaths. Early detection and localization of crisis-related events can help save lives and economies. Yet, the applied automation methods introduce ethical risks worthy of investigation - especially given their high-stakes societal context. This work identifies and critically examines ethical risk factors of social media analyses of crisis events focusing on machine learning methods. We aim to sensitize researchers and practitioners to the ethical pitfalls and promote fairer and more reliable designs.

AB - Social media platforms provide a continuous stream of real-time news regarding crisis events on a global scale. Several machine learning methods utilize the crowd-sourced data for the automated detection of crises and the characterization of their precursors and aftermaths. Early detection and localization of crisis-related events can help save lives and economies. Yet, the applied automation methods introduce ethical risks worthy of investigation - especially given their high-stakes societal context. This work identifies and critically examines ethical risk factors of social media analyses of crisis events focusing on machine learning methods. We aim to sensitize researchers and practitioners to the ethical pitfalls and promote fairer and more reliable designs.

KW - artificial intelligence

KW - crisis informatics

KW - ethics

KW - machine learning

KW - risks

KW - social media

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=85156108349&partnerID=8YFLogxK

M3 - Article in conference proceedings

AN - SCOPUS:85156108349

VL - 3376

T3 - CEUR Workshop Proceedings

BT - Data-driven Resilience Research 2022

A2 - Arndt, Natanael

A2 - Gründer-Fahrer, Sabine

A2 - Holze, Julia

A2 - Martin, Michael

A2 - Tramp, Sebastian

PB - Sun Site Central Europe (RWTH Aachen University)

T2 - 2022 International Workshop on Data-Driven Resilience Research - D2R2 2022

Y2 - 6 July 2022 through 6 July 2022

ER -

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