short-paper

Community-centric analysis of user engagement in Skype social network

Authors:

Giulio Rossetti,

Luca Pappalardo,

Dino Pedreschi,

Fosca Giannotti,

Marlon DumasAuthors Info & Claims

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

Pages 547 - 552

https://doi.org/10.1145/2808797.2809384

Published: 25 August 2015 Publication History

Abstract

Traditional approaches to user engagement analysis focus on individual users. In this paper we address user engagement analysis at the level of groups of users (social communities). From the entire Skype social network we extract communities by means of representative community detection methods each one providing node partitions having their own peculiarities. We then examine user engagement in the extracted communities putting into evidence clear relations between topological and geographic features of communities and their mean user engagement. In particular we show that user engagement can be to a great extent predicted from such features. Moreover, from the analysis it clearly emerges that the choice of community definition and granularity deeply affect the predictive performance.

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Cited By

Cai TYang SLi JSheng QYang JWang XZhang WGao L(2022)Incremental Graph Computation: Anchored Vertex Tracking in Dynamic Social NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3199494(1-14)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3199494
Mishra SSingh SMishra SBiswas B(2021)TCD2: Tree-based community detection in dynamic social networksExpert Systems with Applications10.1016/j.eswa.2020.114493169(114493)Online publication date: May-2021
https://doi.org/10.1016/j.eswa.2020.114493
Cai TLi JHasan Haldar NMian AYearwood JSellis T(2020)Anchored Vertex Exploration for Community Engagement in Social Networks2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00042(409-420)Online publication date: Apr-2020
https://doi.org/10.1109/ICDE48307.2020.00042
Show More Cited By

Community-centric analysis of user engagement in Skype social network
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
2. Information systems
  1. Information systems applications

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cover image ACM Conferences

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

August 2015

835 pages

ISBN:9781450338547

DOI:10.1145/2808797

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 25 August 2015

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Short-paper
Research
Refereed limited

Funding Sources

European Commission
Microsoft/Skype and ERDF

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ASONAM '15

Sponsor:

SIGKDD

ASONAM '15: Advances in Social Networks Analysis and Mining 2015

August 25 - 28, 2015

Paris, France

Acceptance Rates

Overall Acceptance Rate 116 of 549 submissions, 21%

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Citations

Cited By

Cai TYang SLi JSheng QYang JWang XZhang WGao L(2022)Incremental Graph Computation: Anchored Vertex Tracking in Dynamic Social NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3199494(1-14)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3199494
Mishra SSingh SMishra SBiswas B(2021)TCD2: Tree-based community detection in dynamic social networksExpert Systems with Applications10.1016/j.eswa.2020.114493169(114493)Online publication date: May-2021
https://doi.org/10.1016/j.eswa.2020.114493
Cai TLi JHasan Haldar NMian AYearwood JSellis T(2020)Anchored Vertex Exploration for Community Engagement in Social Networks2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00042(409-420)Online publication date: Apr-2020
https://doi.org/10.1109/ICDE48307.2020.00042
Rossetti G(2020)ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networksApplied Network Science10.1007/s41109-020-00270-65:1Online publication date: 10-Jun-2020
https://doi.org/10.1007/s41109-020-00270-6
Guidotti RRossetti G(2020)“Know Thyself” How Personal Music Tastes Shape the Last.Fm Online Social NetworkFormal Methods. FM 2019 International Workshops10.1007/978-3-030-54994-7_11(146-161)Online publication date: 13-Aug-2020
https://doi.org/10.1007/978-3-030-54994-7_11
Rossetti G(2019)Exorcising the Demon: Angel, Efficient Node-Centric Community DiscoveryComplex Networks and Their Applications VIII10.1007/978-3-030-36687-2_13(152-163)Online publication date: 26-Nov-2019
https://doi.org/10.1007/978-3-030-36687-2_13
Tagarelli AInterdonato RTagarelli AInterdonato R(2018)DelurkingMining Lurkers in Online Social Networks10.1007/978-3-030-00229-9_6(47-65)Online publication date: 10-Nov-2018
https://doi.org/10.1007/978-3-030-00229-9_6
Verma RSehgal VNitin (2017)Crisis Management Using Centrality Measurement in Social NetworksInternational Journal of Mobile Computing and Multimedia Communications10.4018/IJMCMC.20170101028:1(19-33)Online publication date: Jan-2017
https://doi.org/10.4018/IJMCMC.2017010102
Rossetti GPappalardo LPedreschi DGiannotti F(2017)TilesMachine Language10.1007/s10994-016-5582-8106:8(1213-1241)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.1007/s10994-016-5582-8
Rossetti GPappalardo LRinzivillo S(2016)A Novel Approach to Evaluate Community Detection Algorithms on Ground TruthComplex Networks VII10.1007/978-3-319-30569-1_10(133-144)Online publication date: 3-Mar-2016
https://doi.org/10.1007/978-3-319-30569-1_10

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