research-article

Organizational overlap on social networks and its applications

Authors:

Deepak Agarwal,

Xinyi (Lisa) Huang,

Sam ShahAuthors Info & Claims

WWW '13: Proceedings of the 22nd international conference on World Wide Web

Pages 571 - 582

https://doi.org/10.1145/2488388.2488439

Published: 13 May 2013 Publication History

Abstract

Online social networks have become important for networking, communication, sharing, and discovery. A considerable challenge these networks face is the fact that an online social network is partially observed because two individuals might know each other, but may not have established a connection on the site. Therefore, link prediction and recommendations are important tasks for any online social network. In this paper, we address the problem of computing edge affinity between two users on a social network, based on the users belonging to organizations such as companies, schools, and online groups. We present experimental insights from social network data on organizational overlap, a novel mathematical model to compute the probability of connection between two people based on organizational overlap, and experimental validation of this model based on real social network data. We also present novel ways in which the organization overlap model can be applied to link prediction and community detection, which in itself could be useful for recommending entities to follow and generating personalized news feed.

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Cited By

Mejia NPerelló JSantos-Boada Gde Almeida Amazonas J(2024)A Multidisciplinary Model to Quantify Human Uncertainty in Human-Centric Cyber-Physical-Social Systems: A 5G Application Use CaseIEEE Access10.1109/ACCESS.2024.339679112(63484-63503)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3396791
Yan XMa AYang JZhu LJing HBollinger JHe QDemartini GZuccon GCulpepper JHuang ZTong H(2021)Contextual Skill Proficiency via Multi-task Learning at LinkedInProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481904(4273-4282)Online publication date: 26-Oct-2021
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Yan XYang JObukhov MZhu LBai JWu SHe QTeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)Social Skill Validation at LinkedInProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330752(2943-2951)Online publication date: 25-Jul-2019
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Index Terms

Organizational overlap on social networks and its applications
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Other conferences

WWW '13: Proceedings of the 22nd international conference on World Wide Web

May 2013

1628 pages

ISBN:9781450320351

DOI:10.1145/2488388

General Chairs:
Daniel Schwabe
PUC-Rio - Brazil
,
Virgílio Almeida
UFMG - Brazil
,
Hartmut Glaser
CGI.br - Brazil
,
Program Chairs:
Ricardo Baeza-Yates
Yahoo! Labs - Spain & Chile
,
Sue Moon
KAIST - South Korea

Copyright © 2013 Copyright is held by the International World Wide Web Conference Committee (IW3C2).

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NICBR: Nucleo de Informatcao e Coordenacao do Ponto BR
CGIBR: Comite Gestor da Internet no Brazil

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 May 2013

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WWW '13: 22nd International World Wide Web Conference

May 13 - 17, 2013

Rio de Janeiro, Brazil

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WWW '13 Paper Acceptance Rate 125 of 831 submissions, 15%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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https://doi.org/10.1109/ACCESS.2024.3396791
Yan XMa AYang JZhu LJing HBollinger JHe QDemartini GZuccon GCulpepper JHuang ZTong H(2021)Contextual Skill Proficiency via Multi-task Learning at LinkedInProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3481904(4273-4282)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3481904
Yan XYang JObukhov MZhu LBai JWu SHe QTeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)Social Skill Validation at LinkedInProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330752(2943-2951)Online publication date: 25-Jul-2019
https://dl.acm.org/doi/10.1145/3292500.3330752
Jing NWu ZLyu SSugumaran V(2019)Information credibility evaluation in online professional social network using tree augmented naïve Bayes classifierElectronic Commerce Research10.1007/s10660-019-09387-yOnline publication date: 15-Nov-2019
https://doi.org/10.1007/s10660-019-09387-y
Segev NAvigdor NAvigdor ECollins-Thompson KMei QDavison BLiu YYilmaz E(2018)Measuring Influence on InstagramThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval10.1145/3209978.3210134(1009-1012)Online publication date: 27-Jun-2018
https://dl.acm.org/doi/10.1145/3209978.3210134
Pham HShahabi CLiu Y(2016)Inferring Social Strength from Spatiotemporal DataACM Transactions on Database Systems10.1145/287720041:1(1-47)Online publication date: 18-Mar-2016
https://dl.acm.org/doi/10.1145/2877200
Tsai CLin YBourdeau JHendler JNkambou RHorrocks IZhao B(2016)Tracing and Predicting Collaboration for Junior ScholarsProceedings of the 25th International Conference Companion on World Wide Web10.1145/2872518.2890516(375-380)Online publication date: 11-Apr-2016
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Digiampietri LMaruyama WSantiago CLima JSiqueira SCarvalho S(2015)A Link Prediction System in Social NetworksProceedings of the annual conference on Brazilian Symposium on Information Systems: Information Systems: A Computer Socio-Technical Perspective - Volume 110.5555/2814058.2814082(139-146)Online publication date: 26-May-2015
https://dl.acm.org/doi/10.5555/2814058.2814082
Zhang JLv YYu PBailey JMoffat AAggarwal Cde Rijke MKumar RMurdock VSellis TYu J(2015)Enterprise Social Link RecommendationProceedings of the 24th ACM International on Conference on Information and Knowledge Management10.1145/2806416.2806549(841-850)Online publication date: 17-Oct-2015
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Tiwari MSchwabe DAlmeida VGlaser HBaeza-Yates RMoon S(2013)Large-scale social recommender systemsProceedings of the 22nd International Conference on World Wide Web10.1145/2487788.2488086(939-940)Online publication date: 13-May-2013
https://dl.acm.org/doi/10.1145/2487788.2488086

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