Influence maximization-based event organization on social networks

研究成果: Conference contribution

摘要

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.

原文English
主出版物標題Personal Analytics and Privacy
主出版物子標題An Individual and Collective Perspective - 1st International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Revised Selected Papers
編輯Riccardo Guidotti, Anna Monreale, Dino Pedreschi, Serge Abiteboul
發行者Springer Verlag
頁面155-158
頁數4
ISBN(列印)9783319719696
DOIs
出版狀態Published - 2017 一月 1
事件1st 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
持續時間: 2017 九月 182017 九月 18

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10708 LNCS
ISSN(列印)0302-9743
ISSN(電子)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
國家Macedonia, The Former Yugoslav Republic of
城市Skopje
期間17-09-1817-09-18

指紋

Social Networks
Heuristic methods
Communication
Labels
Costs
Experiments
Influence
Communication Cost
Heuristic Method
Greedy Algorithm
NP-complete problem
Predict
Vertex of a graph

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

引用此文

Li, C. T. (2017). Influence maximization-based event organization on social networks. 於 R. Guidotti, A. Monreale, D. Pedreschi, & S. Abiteboul (編輯), Personal Analytics and Privacy: An Individual and Collective Perspective - 1st International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Revised Selected Papers (頁 155-158). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10708 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-71970-2_13
Li, Cheng Te. / Influence maximization-based event organization on social networks. Personal Analytics and Privacy: An Individual and Collective Perspective - 1st International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Revised Selected Papers. 編輯 / Riccardo Guidotti ; Anna Monreale ; Dino Pedreschi ; Serge Abiteboul. Springer Verlag, 2017. 頁 155-158 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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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.",
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Li, CT 2017, Influence maximization-based event organization on social networks. 於 R Guidotti, A Monreale, D Pedreschi & S Abiteboul (編輯), Personal Analytics and Privacy: An Individual and Collective Perspective - 1st International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 10708 LNCS, Springer Verlag, 頁 155-158, 1st 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, 17-09-18. https://doi.org/10.1007/978-3-319-71970-2_13

Influence maximization-based event organization on social networks. / Li, Cheng Te.

Personal Analytics and Privacy: An Individual and Collective Perspective - 1st International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Revised Selected Papers. 編輯 / Riccardo Guidotti; Anna Monreale; Dino Pedreschi; Serge Abiteboul. Springer Verlag, 2017. p. 155-158 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10708 LNCS).

研究成果: Conference contribution

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Li CT. Influence maximization-based event organization on social networks. 於 Guidotti R, Monreale A, Pedreschi D, Abiteboul S, 編輯, Personal Analytics and Privacy: An Individual and Collective Perspective - 1st International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Revised Selected Papers. Springer Verlag. 2017. p. 155-158. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-71970-2_13