Abstract
As a sociological phenomenon, rumor spreading has been widely researched by sociologists and other fields’ scholars. How do people generate those strange thinking about the rumor? This paper, from artificial intelligence view, focuses on an algorithm based on Hierarchical Temporal Memory (HTM) to simulate human cognitive process of generating rumors from individual heterogeneous living experience. Comparison with classical Bayesian Networks, our algorithm could effectively and really simulate human cognitive process of rumors, and in accordance with some typical psychology effects proved by sociologists and psychologists.
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References
Galam, S.: Modeling rumors: the no plane Pentagon French hoax case. J. Physica A: Statistical Mechanics and Its Applications 320, 571–580 (2003)
Nekovee, M., Moreno, Y., Bianconi, G., et al.: Theory of rumour spreading in complex social networks. J. Physica A: Statistical Mechanics and its Applications 374(1), 457–470 (2007)
Kawachi, K.: Deterministic models for rumor transmission. J. Nonlinear Analysis: Real World Applications 9(5), 1989–2028 (2008)
Kawachi, K., Sek, I.M., Yoshida, H., et al.: A rumor transmission model with various contact interactions. J. Journal of Theoretical Biology 253(1), 55–60 (2008)
Daley, D.J., Kendall, D.G.: Stochastic rumours. J. IMA Journal of Applied Mathematics 1(1), 42–55 (1965)
Kim, J.H., Bock, G.W.C.: A Study On The Factors Affecting The Behavior Of Spreading Online Rumors: Focusing On the Rumor Recipient’s Emotions. In: PACIS 2011 Proceedings, pp. 98–104 (2011)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. J. Nature 393(6684), 440–442 (1998)
Zhao, L., Wang, Q., Cheng, J., et al.: The impact of authorities’ media and rumor dissemination on the evolution of emergency. J. Physica A: Statistical Mechanics and its Applications 391(15), 3978–3987 (2012)
Murphy, K.P.: Dynamic Bayesian networks: representation, inference and learning. D. University of California (2002)
Numenta, Inc.: Hierarchical Temporal Memory Comparison with Existing Models (2007)
George, D., Jaros, B.: The HTM learning algorithms (2007), http://numenta.com
Hawkins, J., George, D.: Hierarchical temporal memory: Concepts, theory and terminology. J. Whitepaper, NumentaInc (2006)
Rozado, D., Rodriguez, F.B., Varona, P.: Extending the bioinspired hierarchical temporal memory paradigm for sign language recognition. J. Neurocomputing 79, 75–86 (2012)
Rozado, D., Rodriguez, F.B., Varona, P.: Low cost remote gaze gesture recognition in real time. J. Applied Soft Computing 12(8), 2072–2084 (2012)
Asch, S.E.: Forming impressions of personality. J. The Journal of Abnormal and Social Psychology 41(3), 258 (1946)
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Li, X., Chen, X., Wang, W. (2014). A Research on Human Cognitive Modeling in Rumor Spreading Based on HTM. In: Ma, S., Jia, L., Li, X., Wang, L., Zhou, H., Sun, X. (eds) Life System Modeling and Simulation. ICSEE LSMS 2014 2014. Communications in Computer and Information Science, vol 461. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45283-7_28
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DOI: https://doi.org/10.1007/978-3-662-45283-7_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45282-0
Online ISBN: 978-3-662-45283-7
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