Dyadic event attribution in social networks with mixtures of Hawkes processes

International Conference on Information and Knowledge Management, Proceedings

Volumn , Issue , 2013, Pages 1667-1672

  Li, Liangda ^a   Zha, Hongyuan ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

Dyadic event; Hawkes process; International armed conflicts; Missing data problem; Variational inference

Indexed keywords

ARMED CONFLICT; DYADIC EVENT; HEURISTIC RULES; MISSING DATA PROBLEM; MODEL PARAMETERS; NETWORK PARAMETERS; PROBABILISTIC MODELING; VARIATIONAL INFERENCE;

KNOWLEDGE MANAGEMENT; MIXTURES; VIRTUAL REALITY;

SOCIAL NETWORKING (ONLINE);

EID: 84889599734     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2505515.2505609     Document Type: Conference Paper

References (18)

1. ACLED. http://www.acleddata.com, 2010.
2. Y. Ait-Sahalia, J. Cacho-Diaz, and R. Laeven. Modeling financial contagion using mutually exciting jump processes. Tech. rep., 2010.
3. Y.-S. Cho, A. Galstyan, J. Brantingham, and G. Tita. Latent point process models for spatial-temporal networks. In Manuscript, 2013.
4. R. Crane and D. Sornette. Robust dynamic classes revealed by measuring the response function of a social system. Proceedings of the National Academy of Sciences of the United States of America, 105(41):15649-15653, 2008.
5. E. Errais, K. Giesecke, and L. R. Goldberg. Affine point processes and portfolio credit risk. SIAM J. Fin. Math., 1(1):642-665, Sep 2010.
6. M. G.-Rodriguez, D. Balduzzi, and B. Schölkopf. Uncovering the temporal dynamics of diffusion networks. In ICML, pages 561-568, 2011.
7. A. G. Hawkes. Spectra of some self-exciting and mutually exciting point processes. Biometrika, 58:83-90, 1971.
8. R. A. Hegemann, E. A. Lewis, and A. L. Bertozzi. An "estimate & score algorithm" for simultaneous parameter estimation and reconstruction of missing data on social networks. accepted in Security Informatics., 2012.
9. D. A. Kashy and D. A. Kenny. The analysis of data from dyads and groups. In H. Reis & C. M. Judd (Eds.), Handbook of research methods in social psychology, page 451477, 2000.
10. D. A. Kenny. Dyadic analysis. The SAGE Encyclopedia of Social Science Research Methods, 2004.
11. E. Lewisa and G. Mohlerb. A nonparametric em algorithm for multiscale hawkes processes. Journal of Nonpara-metric Statistics, 1, 2011.
12. T. J. Liniger. Multivariate hawkes processes. ETH Doctoral Dissertation, (18403), 2009.
13. Y Ogata. Statistical models for earthquake occurrences and residual analysis for point processes. Journal of the American Statistical Association., 83(401):9-27, 1988.
14. M. D. Porter and G. White. Self-exciting hurdle models for terrorist activity. The Annals of Applied Statistics, 6(1):106-124, 2011.
15. C. Raleigh, A. Linke, H. Hegre, and J. Karlsen. Introducing acled: An armed conflict location and event dataset special data feature. Journal of Peace Research, 47(5):651-660, July 2010.
16. A. Stomakhin, M. B. Short, and A. L. Bertozzi. Reconstruction of missing data in social networks based on temporal patterns of interactions. Inverse Problems., 27(11), Nov 2011.
17. D. Q. Vu, A. U. Asuncion, D. R. Hunter, and P. Smyth. Dynamic egocentric models for citation networks. In ICML, pages 857-864, 2011.
18. A. Z.-Mangion, M. Dewarc, V. Kadirkamanathand, and G. Sanguinetti. Point process modelling of the afghan war diary. PNAS, 109(31):12414-12419, July 2012.