A budget feasible mechanism for k-topic influence maximization in social networks

Yuhui Zhang, Ming Li, Dejun Yang, Guoliang Xue

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

3 Scopus citations

Abstract

The past decade has seen vast research on the influence maximization problem in social networks: How to select a subset of individuals to become initial adopters, so that the word-of-mouth effect in the social network is maximized Approximation algorithms have been proposed for this NP-hard problem with knapsack or other constraints. To incentivize influencers to become initial adopters, Singer has initiated budget feasible mechanisms. In this paper, we generalize them to the budget feasible mechanism for k-topic influence maximization problem. We investigate this problem and propose KIMI. We rigorously prove that KIMI achieves 5e/(e-1) approximation and computational efficiency, individual rationality, truthfulness, budget feasibility. Extensive simulations demonstrate that KIMI significantly outperforms baseline methods.

Original languageEnglish (US)
Title of host publication2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728109626
DOIs
StatePublished - Dec 2019
Event2019 IEEE Global Communications Conference, GLOBECOM 2019 - Waikoloa, United States
Duration: Dec 9 2019Dec 13 2019

Publication series

Name2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings

Conference

Conference2019 IEEE Global Communications Conference, GLOBECOM 2019
Country/TerritoryUnited States
CityWaikoloa
Period12/9/1912/13/19

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Signal Processing
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Media Technology
  • Health Informatics

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