Mitigating demographic bias of machine learning models on social media-Reference-Cited by-同舟云学术

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Mitigating demographic bias of machine learning models on social media

Published:2023-10-30 Issue: Volume: Page:
ISSN:
Container-title:Equity and Access in Algorithms, Mechanisms, and Optimization
language:
Short-container-title:

Author:

Wang Yanchen¹^ORCID,Singh Lisa¹^ORCID

Affiliation:

1. Georgetown University, USA

Funder

National Science Foundation

Massive Data Institute

National Collaborative on Gun Violence Research

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3617694.3623244

Reference64 articles.

1. Detection and classification of social media-based extremist affiliations using sentiment analysis techniques;Ahmad Shakeel;Human-centric Computing and Information Sciences,2019

2. Differential Tweetment

3. Big data’s disparate impact;Barocas Solon;California Law Review,2016

4. AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias

5. Richard Berk Hoda Heidari Shahin Jabbari Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel and Aaron Roth. 2017. A convex framework for fair regression. arxiv:1706.02409 Richard Berk Hoda Heidari Shahin Jabbari Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel and Aaron Roth. 2017. A convex framework for fair regression. arxiv:1706.02409

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