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Social Circle Discovery in Ego-Networks by Mining the Latent Structure of User Connections and Profile Attributes

Authors:

Georgios Petkos,

Symeon Papadopoulos,

Yiannis KompatsiarisAuthors Info & Claims

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

Pages 880 - 887

https://doi.org/10.1145/2808797.2809303

Published: 25 August 2015 Publication History

Abstract

Online Social Networks (OSN) allow their users to organize their friends into groups, also known as social circles. These social circles can be used to better manage who has access to users' posted content and also to control the content posted from other users that they view. Unfortunately, these social circles are generated manually and this can be a laborious process for users with more than a few friends. In this paper, we propose an approach for automatically generating social circles that takes into account both the profile information of the friends to be grouped and the social network connectivity between them, while it allows multiple membership of friends in social circles. The approach is based on an adaptation of the widely used Latent Dirichlet Allocation model and, despite the fact that it does not explicitly model social network connectivity, as other state of the art methods do, it manages to achieve results that are competitive and even better than those obtained from such methods, at a considerably lower computational cost.

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Cited By

Zheng PHuang ZDou YYan Y(2023)Rumor Detection on Social Media through Mining the Social Circles with High HomogeneityInformation Sciences10.1016/j.ins.2023.119083(119083)Online publication date: May-2023
https://doi.org/10.1016/j.ins.2023.119083
Tonge ACaragea C(2020)Image Privacy Prediction Using Deep Neural NetworksACM Transactions on the Web10.1145/338608214:2(1-32)Online publication date: 9-Apr-2020
https://dl.acm.org/doi/10.1145/3386082
Tonge ACaragea C(2019)Privacy-aware Tag Recommendation for Accurate Image Privacy PredictionACM Transactions on Intelligent Systems and Technology10.1145/333505410:4(1-28)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3335054
Show More Cited By

Social Circle Discovery in Ego-Networks by Mining the Latent Structure of User Connections and Profile Attributes
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
2. Information systems
  1. Information retrieval
  2. 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 the author(s) 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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ASONAM '15

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SIGKDD

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

August 25 - 28, 2015

Paris, France

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Overall Acceptance Rate 116 of 549 submissions, 21%

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Cited By

Zheng PHuang ZDou YYan Y(2023)Rumor Detection on Social Media through Mining the Social Circles with High HomogeneityInformation Sciences10.1016/j.ins.2023.119083(119083)Online publication date: May-2023
https://doi.org/10.1016/j.ins.2023.119083
Tonge ACaragea C(2020)Image Privacy Prediction Using Deep Neural NetworksACM Transactions on the Web10.1145/338608214:2(1-32)Online publication date: 9-Apr-2020
https://dl.acm.org/doi/10.1145/3386082
Tonge ACaragea C(2019)Privacy-aware Tag Recommendation for Accurate Image Privacy PredictionACM Transactions on Intelligent Systems and Technology10.1145/333505410:4(1-28)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3335054
Yu JKuang ZZhang BZhang WLin DFan J(2018)Leveraging Content Sensitiveness and User Trustworthiness to Recommend Fine-Grained Privacy Settings for Social Image SharingIEEE Transactions on Information Forensics and Security10.1109/TIFS.2017.278798613:5(1317-1332)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1109/TIFS.2017.2787986
Ding FZhuang Y(2018)Ego-network probabilistic graphical model for discovering on-line communitiesApplied Intelligence10.1007/s10489-018-1137-y48:9(3038-3052)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s10489-018-1137-y
Li XCao YShang YLiu YTan JGuo L(2017)Inferring User Profiles in Online Social Networks Based on Convolutional Neural NetworkKnowledge Science, Engineering and Management10.1007/978-3-319-63558-3_23(274-286)Online publication date: 19-Jul-2017
https://doi.org/10.1007/978-3-319-63558-3_23

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