Why spending more might get you less, dynamic selection of influencers in social networks

Alon Sela, Erez Shmueli, Dima Goldenberg, Irad Ben-Gal

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

Abstract

Many studies in the field of information spread through social networks focus on the detection of influencers. The spread dynamics in most of these studies assumes these influencers are first selected and 'infected' with a message, and then this message spreads through the networks by a viral process. The following work presents some difficulties with this separation between the infection stage and the viral stage, and provides a case where an increased effort spent on the spread of an idea results in lower final rates of spread. Such results can be prevented by the Scheduling Seeding approach. This approach gradually plans the timing of infection for each particular node as the viral process progresses. It outperforms the initial seeding approach, and prevents the occurrence of the counter-intuitive (and unwanted) results where a greater effort results in a less successful spread. A simple but effective heuristics to detect what node to seed and where is provided.

Original languageEnglish
Title of host publication2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509021529
DOIs
StatePublished - 4 Jan 2017
Event2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 - Eilat, Israel
Duration: 16 Nov 201618 Nov 2016

Publication series

Name2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

Conference

Conference2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Country/TerritoryIsrael
CityEilat
Period16/11/1618/11/16

Keywords

  • Information Cascade
  • Linear Threshold
  • Scheduling Seeding
  • Social Networks
  • Viral Marketing

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