Influence Maximization with Fairness at Scale-Reference-Cited by-同舟云学术

Influence Maximization with Fairness at Scale

Published:2023-08-04 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Feng Yuting¹^ORCID,Patel Ankitkumar²^ORCID,Cautis Bogdan³^ORCID,Vahabi Hossein²^ORCID

Affiliation:

1. University Paris-Saclay & CNRS LISN, Orsay, France

2. University of California - Berkeley, Berkeley, CA, USA

3. University Paris-Saclay & CNRS IPAL Singapore, Singapore, Singapore

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599847

Reference30 articles.

1. On the Fairness of Time-Critical Influence Maximization in Social Networks;Ali J.;IEEE Transactions on Knowledge & Data Engineering,2022

2. Social influence maximization under empirical influence models

3. Akhil Arora Sainyam Galhotra and Sayan Ranu. 2017. Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study. In SIGMOD. Akhil Arora Sainyam Galhotra and Sayan Ranu. 2017. Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study. In SIGMOD.

4. Akhil Arora Sainyam Galhotra and Sayan Ranu. 2019. Influence Maximization Revisited: The State of the Art and the Gaps that Remain. In EDBT. Akhil Arora Sainyam Galhotra and Sayan Ranu. 2019. Influence Maximization Revisited: The State of the Art and the Gaps that Remain. In EDBT.

5. Eytan Bakshy Jake M Hofman Winter A Mason and Duncan J Watts. 2011. Everyone's an influencer: quantifying influence on twitter. In WSDM. Eytan Bakshy Jake M Hofman Winter A Mason and Duncan J Watts. 2011. Everyone's an influencer: quantifying influence on twitter. In WSDM.