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Complex Interactions in Social and Event Network Analysis

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Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9021))

Abstract

Modern social network analytic techniques, such as centrality analysis, outlier detection, and/or segmentation, are limited in that they typically only identify interactions within the dataset occurring as a first-order effect. In our previous work, we illustrated how the use of tensor decomposition can be used to identify multi-way interactions in both sparse and dense data-sets. The primary aim of this paper will be to introduce innovative extensions to our tensor decomposition approach that target and/or identify second and third order effects.

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References

  1. Davidson, I.: Knowledge driven dimension reduction for clustering. IJCAI, 1034–1039 (2009)

    Google Scholar 

  2. Davidson, I., Gilpin, S., Walker, P. B.: Behavioral Event Data and Their Analysis. In: Data Mining & Knowledge Discovery, pp. 635–653 (2012)

    Google Scholar 

  3. Hagen, L., Kahng, A.: New spectral methods for ratio cut partitioning and clustering. IEEE Transactions in Computer-Aided Design 11(9), 1074–1085 (1992)

    Article  Google Scholar 

  4. Stoer, M., Wagner, F.: A simple min-cut algorithm. J. ACM 44(4), 585–591 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  5. Von Luxburg, U.: A Tutorial on Spectral Clustering. Statistics and Computing 17 (4) (2007)

    Google Scholar 

  6. Wagner, D., Wagner, F.: Between min cut and graph bisection. In: Proceedings of the 18th International Symposium on Mathematical Foundations of Computer Science (MFCS), pp. 744–750). Springer, London (1993)

    Google Scholar 

  7. Wang, X., Davidson, I.: Flexible constrained spectral clustering. In: KDD 2010, pp. 563–572 (2010)

    Google Scholar 

  8. Wu, Z., Leahy, R.: An Optimal Graph Theoretic Approach to Data Clustering: Theory and Its Application to Image Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 15 (11), 1,101–1,113 (1993)

    Google Scholar 

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Author information

Authors and Affiliations

  1. United States Navy, Aerospace Experimental Psychology, Michigan, USA

    Peter B. Walker & Sidney G. Fooshee

  2. Department of Computer Science, University of California, Davis, USA

    Ian Davidson

Authors
  1. Peter B. Walker
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  2. Sidney G. Fooshee
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  3. Ian Davidson
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Corresponding author

Correspondence to Peter B. Walker .

Editor information

Editors and Affiliations

  1. University of Arkansas, Little Rock, Arkansas, USA

    Nitin Agarwal

  2. Technicolor Research, Los Altos, California, USA

    Kevin Xu

  3. University of Saskatchewan, Saskatoon, Saskatchewan, Canada

    Nathaniel Osgood

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© 2015 Springer International Publishing Switzerland

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Walker, P.B., Fooshee, S.G., Davidson, I. (2015). Complex Interactions in Social and Event Network Analysis. In: Agarwal, N., Xu, K., Osgood, N. (eds) Social Computing, Behavioral-Cultural Modeling, and Prediction. SBP 2015. Lecture Notes in Computer Science(), vol 9021. Springer, Cham. https://doi.org/10.1007/978-3-319-16268-3_56

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  • DOI: https://doi.org/10.1007/978-3-319-16268-3_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16267-6

  • Online ISBN: 978-3-319-16268-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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