Please be an influencer? Contingency-aware influence maximization

Amulya Yadav, Laura Onasch-Vera, Ritesh Noothigattu, Leandro Soriano Marcolino, Eric Rice, Milind Tambe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most previous work on influence maximization in social networks assumes that the chosen influencers (or seed nodes) can be influenced with certainty (i.e., with no contingencies). In this paper, we focus on using influence maximization in public health domains for assisting low-resource communities, where contingencies are common. It is very difficult in these domains to ensure that the seed nodes are influenced, as influencing them entails contacting/convincing them to attend training sessions, which may not always be possible. Unfortunately, previous state-of-the-art algorithms for influence maximization are unusable in this setting. This paper tackles this challenge via the following four contributions: (i) we propose the Contingency Aware Influence Maximization problem and analyze it theoretically; (ii) we cast this problem as a Partially Observable Markov Decision Process and propose CAIMS (a novel POMDP planner) to solve it, which leverages a natural action space factorization associated with real-world social networks; and (iii) we provide extensive simulation results to compare CAIMS with existing state-of-the-art influence maximization algorithms. Finally, (iv) we provide results from a real-world feasibility trial conducted to evaluate CAIMS, in which key influencers in homeless youth social networks were influenced in order to spread awareness about HIV.

Original languageEnglish (US)
Title of host publication17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1423-1431
Number of pages9
ISBN (Print)9781510868083
StatePublished - Jan 1 2018
Event17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 - Stockholm, Sweden
Duration: Jul 10 2018Jul 15 2018

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
Volume2
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Other

Other17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018
CountrySweden
CityStockholm
Period7/10/187/15/18

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Cite this

Yadav, A., Onasch-Vera, L., Noothigattu, R., Marcolino, L. S., Rice, E., & Tambe, M. (2018). Please be an influencer? Contingency-aware influence maximization. In 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018 (pp. 1423-1431). (Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS; Vol. 2). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).