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abstract

Testing Higher-Order Network Structures in an Online Experiment

Published: 27 February 2016 Publication History

Abstract

Currently, the de facto representational choice for networks is graphs which capture pairwise relationships between entities. This dyadic approach fails to adequate capture the array of group relationships that are more than the sum of their parts and prevalent in real-world situations. For example, collaborative teams, wireless broadcast, and political coalitions all contain unique group dynamics that need to be captured. In this paper, we use simplicial complexes to model these supra-dyadic relationships in networks. We argue that a number of problems within social and communications networks such as network-wide broadcast and collaborative teams can be elegantly captured using simplicial complexes in a way that is not possible with graphs. In this study, we operationalize several types of simplicial complexes in an online-based experiment using the Wildcat Wells paradigm. We then run subjects in these experiments to investigate measures of team strength and hub behavior using simplicial complex models.

References

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Ram. Ramanathan, A. Bar-Noy, P. Basu, M. Johnson, W. Ren, A. Swami, and Q. Zhao. 2011 Beyond graphs: Capturing groups in networks. In International Workshop on Network Science for Communication Networks, Proceedings of the IEEE. 870-875.
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T. Moore, R. Drost, P. Basu, Ram. Ramanathan, and A. Swami. 2012. Analyzing collaboration networks using simplicial complexes: A case study. In International Workshop on Network Science for Communication Networks, Proceedings of the IEEE. NetSciComm. 238-243.
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Claude Berge, Hypergraphs. North-Holland, 1989.
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Wojciech Matusik, Matthias Zwicker, and Fredo Durand. 2005. Texture design using a simplicial complex of morphable textures, ACM Transactions on Graphics, 24, 3, 787-794.
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Alireza Tahbaz-Salehi and Ali Jadbabaie. 2010. Distributed coverage verification in sensor networks without location information. In IEEE Transactions on Automatic Control, 55, 1837-1849.
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Winter Mason and Duncan J. Watts. 2012 Collaborative learning in networks. In Proceedings of the National Academy of Sciences, 109, 3, 764- 769.

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cover image ACM Conferences
CSCW '16 Companion: Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion
February 2016
549 pages
ISBN:9781450339506
DOI:10.1145/2818052
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 February 2016

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Author Tags

  1. Computer Science
  2. Groups
  3. Networks
  4. Online Experimentation
  5. Problem Solving

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CSCW '16
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CSCW '16: Computer Supported Cooperative Work and Social Computing
February 26 - March 2, 2016
California, San Francisco, USA

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