Improving information spread through a scheduled seeding approach

Alon Sela, Irad Ben-Gal, Alex Sandy Pentland, Erez Shmueli

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

21 Scopus citations

Abstract

One highly studied aspect of social networks is the identification of influential nodes that can spread ideas in a highly efficient way. The vast majority of works in this field have investigated the problem of identifying a set of nodes, that if "seeded" simultaneously, would maximize the information spread in the network. Yet, the timing aspect, namely, finding not only which nodes should be seeded but also when to seed them, has not been sufficiently addressed. In this work, we revisit the problem of network seeding and demonstrate by simulations how an approach takes takes into account the timing aspect, can improve the rates of spread by over 23% compared to existing seeding methods. Such an approach has a wide range of applications, especially in cases where the network topology is easily accessible.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
EditorsJian Pei, Jie Tang, Fabrizio Silvestri
Pages629-632
Number of pages4
ISBN (Electronic)9781450338547
DOIs
StatePublished - 25 Aug 2015
Externally publishedYes
EventIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015 - Paris, France
Duration: 25 Aug 201528 Aug 2015

Publication series

NameProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015

Conference

ConferenceIEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
Country/TerritoryFrance
CityParis
Period25/08/1528/08/15

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