Multi-objective influence maximization

Shay Gershtein, Tova Milo, Brit Youngmann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Influence Maximization (IM) is the problem of finding a set of influential users in a social network, so that their aggregated influence is maximized. The classic IM problem focuses on the single objective of maximizing the overall number of influenced users. While this serves the goal of reaching a large audience, users often have multiple specific sub-populations they would like to reach within a single campaign, and consequently multiple influence maximization objectives. As we show, maximizing the influence over one group may come at the cost of significantly reducing the influence over the others. To address this, we propose IM-Balanced, a system that allows users to explicitly declare the desired balance between the objectives. IM-Balanced employs a refined notion of the classic IM problem, called Multi-Objective IM, where all objectives except one are turned into constraints, and the remaining objective is optimized subject to these constraints. We prove Multi-Objective IM to be harder to approximate than the original IM problem, and correspondingly provide two complementary approximation algorithms, each suiting a different prioritization pertaining to the inherent trade-off between the objectives. In our experiments we compare our solutions both to existing IM algorithms as well as to alternative approaches, demonstrating the advantages of our algorithms.

Original languageEnglish
Title of host publicationAdvances in Database Technology - EDBT 2021
Subtitle of host publication24th International Conference on Extending Database Technology, Proceedings
EditorsYannis Velegrakis, Yannis Velegrakis, Demetris Zeinalipour, Panos K. Chrysanthis, Panos K. Chrysanthis, Francesco Guerra
Number of pages12
ISBN (Electronic)9783893180844
StatePublished - 2021
EventAdvances in Database Technology - 24th International Conference on Extending Database Technology, EDBT 2021 - Virtual, Nicosia, Cyprus
Duration: 23 Mar 202126 Mar 2021

Publication series

NameAdvances in Database Technology - EDBT
ISSN (Electronic)2367-2005


ConferenceAdvances in Database Technology - 24th International Conference on Extending Database Technology, EDBT 2021
CityVirtual, Nicosia


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