Influence maximization-based event organization on social networks

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

Abstract

This paper is an ongoing work, and was presented as “Lightening Talk” in the DyNo workshop held at ECML/PKDD 2017. Online event-based social services allow users to organize social events by specifying the themes, and invite friends to participate social events. While the event information can be spread over the social network, it is expected that by certain communication between event hosts, users interested in the event themes can be as many as possible. In this work, by combining the ideas of team formation and influence maximization, we formulate a novel research problem, Influential Team Formation (ITF), to facilitate the organization of social events. Given a set L of required labels to describe the event topics, a social network, and the size k of the host team, ITF is to find a k-node set S that satisfying L and maximizing the Influence-Cost Ratio (i.e., the influence spread per communication cost between team members). Since ITF is proved to be NP-hard, we develop two greedy algorithms and one heuristic method to solve it. Extensive experiments conducted on Facebook and Google+ datasets exhibit the effectiveness and efficiency of the proposed methods. In addition, by employing the real event participation data in Meetup, we show that ITF with the proposed solutions is able to predict organizers of influential events.

Original languageEnglish
Title of host publicationPersonal Analytics and Privacy
Subtitle of host publicationAn Individual and Collective Perspective - 1st International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Revised Selected Papers
EditorsRiccardo Guidotti, Anna Monreale, Dino Pedreschi, Serge Abiteboul
PublisherSpringer Verlag
Pages155-158
Number of pages4
ISBN (Print)9783319719696
DOIs
Publication statusPublished - 2017 Jan 1
Event1st International Workshop on Personal Analytics and Privacy, PAP 2017, Held in Conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2017 - Skopje, Macedonia, The Former Yugoslav Republic of
Duration: 2017 Sep 182017 Sep 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10708 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Personal Analytics and Privacy, PAP 2017, Held in Conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2017
CountryMacedonia, The Former Yugoslav Republic of
CitySkopje
Period17-09-1817-09-18

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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