short-paper

On the predictability of recurring links in networks of face-to-face proximity

Authors:

Christoph Scholz,

Martin Atzmueller,

Gerd StummeAuthors Info & Claims

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

Pages 637 - 642

https://doi.org/10.1145/2567948.2579235

Published: 07 April 2014 Publication History

Abstract

This paper focuses on the predictability of recurring links: These links are generated repeatedly in a network for different forms of social ties, e.g. by face-to-face interactions in offline social networks. In particular, we analyse the predictability of recurring links in networks of face-to-face proximity using several path-based measures, and compare these to network-proximity measures based on the nodes' neighbourhood. Furthermore, we show that the current tie strength is a good predictor for this link prediction task. In addition we show that the removal of weak ties improves the predictability for most of the considered network proximity measures. For our analysis we utilize three real-world datasets collected at different scientific conferences using the Conferator (http://www.conferator.org) system.

References

[1]

M. Atzmueller, S. Doerfel, A. Hotho, F. Mitzlaff, and G. Stumme. Face-to-Face Contacts at a Conference: Dynamics of Communities and Roles. In Modeling and Mining Ubiquitous Social Media, volume 7472 of LNAI. Springer Verlag, Heidelberg, Germany, 2012.

Digital Library

[2]

L. Backstrom and J. Leskovec. Supervised Random Walks: Predicting and Recommending Links in Social Networks. In Proc. WSDM, pages 635--644, New York, NY, USA, 2011. ACM Press.

Digital Library

[3]

A.-L. Barabasi. Linked the New Science of Networks. Perseus Pub., Cambridge, Mass., 2002.

Digital Library

[4]

A. Barrat, C. Cattuto, V. Colizza, J.-F. Pinton, W. V. den Broeck, and A. Vespignani. High Resolution Dynamical Mapping of Social Interactions with Active RFID. CoRR, abs/0811.4170, 2008.

[5]

S. Brin and L. Page. The Anatomy of a Large-Scale Hypertextual Web Search Engine. Computer Networks, 30(1-7):107--117, 1998.

Digital Library

[6]

C. Cattuto, W. Van den Broeck, A. Barrat, V. Colizza, J.-F. Pinton, and A. Vespignani. Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks. PLoS ONE, 5(7):e11596, 07 2010.

[7]

Christoph Scholz and Martin Atzmueller and Alain Barrat and Ciro Cattuto and Gerd Stumme. New Insights and Methods For Predicting Face-To-Face Contacts. In Proc. 7th Intl. Conf. on Weblogs and Social Media, Palo Alto, CA, USA, 2013. AAAI Press.

[8]

J. A. Hanley and B. J. McNeil. The Meaning and Use of the Area under a Receiver Operating Characteristic (ROC) Curve. Radiology, 143(1):29--36, Apr. 1982.

[9]

L. Isella, J. Stehlé, A. Barrat, C. Cattuto, J.-F. Pinton, and W. V. D. Broeck. What's in a crowd? analysis of face-to-face behavioral networks. Journal of Theoretical Biology, 271:166--180, 2011.

[10]

L. Katz. A New Status Index Derived from Sociometric Analysis. Psychometrika, 18(1):39--43, March 1953.

[11]

D. Liben-Nowell and J. M. Kleinberg. The Link Prediction Problem for Social Networks. In CIKM, pages 556--559, 2003.

Digital Library

[12]

R. Lichtenwalter, J. T. Lussier, and N. V. Chawla. New Perspectives and Methods in Link Prediction. In KDD, pages 243--252, 2010.

Digital Library

[13]

B.-E. Macek, C. Scholz, M. Atzmueller, and G. Stumme. Anatomy of a Conference. In Proc. 23rd ACM Conf. on Hypertext and Social Media, pages 245--254, New York, NY, USA, 2012. ACM Press.

Digital Library

[14]

T. Murata and S. Moriyasu. Link Prediction of Social Networks Based on Weighted Proximity Measures. In Web Intelligence, pages 85--88, 2007.

Digital Library

[15]

C. Scholz, M. Atzmueller, and G. Stumme. On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties. In Proc. SocialCom, Boston, MA, USA, 2012. IEEE Computer Society.

Digital Library

[16]

M. Szomszor, C. Cattuto, W. V. den Broeck, A. Barrat, and H. Alani. Semantics, Sensors, and the Social Web: The Live Social Semantics Experiments. In ESWC, pages 196--210, 2010.

Digital Library

[17]

S. Tsugawa and H. Ohsaki. Effectiveness of Link Prediction for Face-to-Face Behavioral Networks. PLoS ONE, 8(12):e81727, 12 2013.

Cited By

Guven CSeipel DAtzmueller M(2021)Applying ASP for Knowledge-Based Link Prediction With Explanation Generation in Feature-Rich NetworksIEEE Transactions on Network Science and Engineering10.1109/TNSE.2020.30475808:2(1305-1315)Online publication date: 1-Apr-2021
https://doi.org/10.1109/TNSE.2020.3047580
Güven ÇAtzmueller M(2019)Applying Answer Set Programming for Knowledge-Based Link Prediction on Social Interaction NetworksFrontiers in Big Data10.3389/fdata.2019.000152Online publication date: 26-Jun-2019
https://doi.org/10.3389/fdata.2019.00015
TSUGAWA S(2019)A Survey of Social Network Analysis Techniques and their Applications to Socially Aware NetworkingIEICE Transactions on Communications10.1587/transcom.2017EBI0003E102.B:1(17-39)Online publication date: 1-Jan-2019
https://doi.org/10.1587/transcom.2017EBI0003
Show More Cited By

Index Terms

On the predictability of recurring links in networks of face-to-face proximity
1. Applied computing
  1. Law, social and behavioral sciences
    1. Sociology
2. Computing methodologies
  1. Machine learning

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Information & Contributors

Information

Published In

cover image ACM Other conferences

WWW '14 Companion: Proceedings of the 23rd International Conference on World Wide Web

April 2014

1396 pages

ISBN:9781450327459

DOI:10.1145/2567948

General Chair:
Chin-Wan Chung
Korea Advanced Institute of Science and Technology, Korea
,
Program Chairs:
Andrei Broder
Google Inc., USA
,
Kyuseok Shim
Seoul National University, Korea
,
Torsten Suel
New York University, USA

Copyright © 2014 Copyright is held by the International World Wide Web Conference Committee (IW3C2).

Sponsors

IW3C2: International World Wide Web Conference Committee

In-Cooperation

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

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 April 2014

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Short-paper

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WWW '14

Sponsor:

IW3C2

WWW '14: 23rd International World Wide Web Conference

April 7 - 11, 2014

Seoul, Korea

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

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Cited By

Guven CSeipel DAtzmueller M(2021)Applying ASP for Knowledge-Based Link Prediction With Explanation Generation in Feature-Rich NetworksIEEE Transactions on Network Science and Engineering10.1109/TNSE.2020.30475808:2(1305-1315)Online publication date: 1-Apr-2021
https://doi.org/10.1109/TNSE.2020.3047580
Güven ÇAtzmueller M(2019)Applying Answer Set Programming for Knowledge-Based Link Prediction on Social Interaction NetworksFrontiers in Big Data10.3389/fdata.2019.000152Online publication date: 26-Jun-2019
https://doi.org/10.3389/fdata.2019.00015
TSUGAWA S(2019)A Survey of Social Network Analysis Techniques and their Applications to Socially Aware NetworkingIEICE Transactions on Communications10.1587/transcom.2017EBI0003E102.B:1(17-39)Online publication date: 1-Jan-2019
https://doi.org/10.1587/transcom.2017EBI0003
Atzmueller MThiele LStumme GKauffeld S(2018)Analyzing group interaction on networks of face-to-face proximity using wearable sensors2018 IEEE International Conference on Future IoT Technologies (Future IoT)10.1109/FIOT.2018.8325593(1-10)Online publication date: Jan-2018
https://doi.org/10.1109/FIOT.2018.8325593
Shahmohammadi AKhadangi EBagheri A(2016)Presenting new collaborative link prediction methods for activity recommendation in FacebookNeurocomputing10.1016/j.neucom.2016.06.024210:C(217-226)Online publication date: 19-Oct-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.06.024

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