Targeted Influence with Community and Gender-Aware Seeding

Targeted Influence with Community and Gender-Aware Seeding

Styczen, MacIej (Swiss Federal Institute of Technology)
Chen, Bing Jyue (Academia Sinica, Institute of Information Science)
Teng, Ya Wen (Academia Sinica, Institute of Information Science)
Pignolet, Yvonne Anne (The Dfinity Foundation Switzerland)
Chen, Lydia Y. (TU Delft Data-Intensive Systems)
Yang, De Nian (Academia Sinica, Institute of Information Science)

2022

When spreading information over social networks, seeding algorithms selecting users to start the dissemination play a crucial role. The majority of existing seeding algorithms focus solely on maximizing the total number of reached nodes, overlooking the issue of group fairness, in particular, gender imbalance. To tackle the challenge of maximizing information spread on certain target groups, e.g., females, we introduce the concept of the community and gender-aware potential of users. We first show that the network's community structure is closely related to the gender distribution. Then, we propose an algorithm that leverages the information about community structure and its gender potential to iteratively modify a seed set such that the information spread on the target group meets the target ratio. Finally, we validate the algorithm by performing experiments on synthetic and real-world datasets. Our results show that the proposed seeding algorithm achieves not only the target ratio but also the highest information spread, compared to the state-of-the-art gender-aware seeding algorithm.

fairness
influence maximization
social networks

http://resolver.tudelft.nl/uuid:537e380c-9bf5-42dc-af55-b4f0c80c9c1a

https://doi.org/10.1145/3511808.3557708

Association for Computing Machinery (ACM)

2023-07-01

978-1-4503-9236-5

CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management

31st ACM International Conference on Information and Knowledge Management, CIKM 2022, 2022-10-17 → 2022-10-21, Atlanta, United States

International Conference on Information and Knowledge Management, Proceedings

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2022 MacIej Styczen, Bing Jyue Chen, Ya Wen Teng, Yvonne Anne Pignolet, Lydia Y. Chen, De Nian Yang