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2012 | 16 | 2 | 165-183

Article title

The Study of Language and Conversation with Recurrence Analysis Methods

Title variants

Languages of publication

EN

Abstracts

EN
In the last decade we witness an increase in approaching issues in language, and more generally, cognition, from a dynamical standpoint. This theoretical shift necessitates new research methods and statistical / analytical tools. Some of these tools gain popularity and are being applied to language in many of its multifaceted perspectives. Recurrence analysis is one of those methods. Its relative simplicity of application and quite unconstrained statistical assumptions give researchers an insight into the dynamical nature of the phenomena under scrutiny. The aim of this paper is an introduction to this method, a review of its convincing applications in the language research on several levels of language analysis and finally, a reflection on its possible further uses.

Publisher

Year

Volume

16

Issue

2

Pages

165-183

Physical description

Dates

published
2012-12-01
online
2012-12-28

Contributors

  • Institute of Philosophy, Nicolaus Copernicus University, Fosa Staromiejska 1a, 87-100 Toruń, Poland

References

  • Abarbanel, H.D.I (1996). Analysis of observed chaotic data. New-York: Springer.
  • Angus, D., Smith, A.E., & Wiles, J. (2012). Conceptual recurrence plots: Revealing patterns in human discourse. IEEE Transactions on Visualization and Computer Graphics, 18 (6), 988-997.[WoS][Crossref]
  • Angus, D., Watson, B., Smith, A., Gallois, C., & Wiles, J. (2012). Visualising conversa­tion structure across time: Insights into effective doctor-patient consultations. PLoS ONE, 7 (6): e38014.
  • Bassingthwaighte, J., Liebovitch, L., & West, B. (1994). Fractal physiology. New York: Oxford University Press.
  • Burrus, C. (2012). Fast fourier transforms. Retrieved from the Connexions Web site: <http://cnx.org/content/col10550A.22/>
  • Costall, A. (2004). From Darwin to Watson (and cognitivism) and back again: The principle of animal-environment mutuality. Behavior and Philosophy, 32, 179-195
  • Dale, R. & Spivey, M.J. (2006). Unraveling the dyad: Using recurrence analysis to explore patterns of syntactic coordination between children and caregivers in conversation. Language Learning, 56 (3), 391-430.[Crossref]
  • Dale, R. & Spivey, M.J. (2005). Categorical recurrence analysis of child language. In B. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the 27th Conference of the Cognitive Science Society (pp. 530-535). Mahwah, NJ: Lawrence Erlbaum.
  • Eckmann, J.-P., Kamphorst, S.O., & Ruelle, D. (1987). Recurrence plots of dynamical systems. Europhysics Letters, 4, 973-977.[Crossref]
  • Fraser A.M. & Swinney H.L. (1986). Independent coordinates for strange attractors from mutual information. Physical Review A, 33, 1134-1140.[Crossref]
  • Fusaroli, R., Tylen, C., & R^czaszek-Leonardi, J. (under review). Dialogue as synergy.
  • Haken, H. (1983). Synergetics, an introduction: Nonequilibrium phase transitions and self-organization in physics, chemistry, and biology. New York: Springer.
  • Kelso, J.A.S. (1995). Dynamic patterns: The self-organization of brain and behavior. Cambridge: MIT Press.
  • MacWhinney, B. (2000). The CHILDES project: Tools for analyzing talk. Mahwah, NJ: Erlbaum.
  • Orsucci, F., Walter, K., Giuliani, A., Webber, C.L.Jr., & Zbilut J.P. (1999). Orthographic structuring of human speech and texts: Linguistic application of recurrence quantification analysis. International Journal of Chaos Theory and Applica­tions, 4 (2-3), 21-28.
  • Orsucci, F., Giuliani, A., Zbilut, J.P. (2004). Structure & coupling of semiotic sets, In: Experimental Chaos Conference 8, Florence, AIP Conference Proceed­ings, 742 (1), 83-93.
  • Orsucci F., Giuliani, A., Webber, C.L.Jr., Zbilut, J.P., Fonagy, P., & Mazza, M. (2006). Combinatorics and synchronization in natural semiotics. Physica A, 361 (2), 665-676.
  • Pellecchia, G.L. & Shockley, K. (2005). Application of recurrence quantification analysis: Influence of cognitive activity on postural fluctuations. In M.A. Riley & G.C. Van Orden (Eds.), Tutorials in contemporary nonlinear methods for the behavioral sciences (pp. 95-141). Retrieved June 1, 2012, from <http://www.nsf>.gov/sbe/bcs/pac/nmbs/nmbs.jsp
  • Pickering, M. & Garrod, S. 2004. Toward a mechanistic psychology of dialogue. Behavioral and Brain Sciences, 27 (2), 169-190.
  • Port, R., & van Gelder, T. (Eds.) (1995). Mind as motion: Explorations in the dynam­ics of cognition. Cambridge: MIT Press.
  • Ra̧̧czaszek-Leonardi, J. & Cowley, S. (2012). The evolution of language as controlled collectivity. Interaction Studies, 13 (1), 1-16.[WoS][Crossref]
  • Richardson, D.C., Dale R., & Kirkham N.Z. (2007). The art of conversation is coordi­nation: Common ground and the coupling of eye movements during dialogue. Psychological Science, 18 (5), 407-413.[Crossref]
  • Riley, M.A., Balasubramaniam, R., & Turvey, M.T. (1999). Recurrence quantification analysis of postural fluctuations. Gait and Posture, 9, 65-78.
  • Salton, G. (1989). Automatic text processing: The transformation, analysis, and retrieval of information by computer. Boston, MA: Addison-Wesley.
  • Shockley, K., Santana, M.-V., & Fowler, C.A. (2003). Mutual interpersonal postural constraints are involved in cooperative conversation. Journal of Experimental Psychology: Human Perception and Performance, 29, 326-332.[Crossref]
  • Takens, F. (1981). Detecting strange attractors in turbulence. In D. Rand & L.-S. Young (Eds.), Dynamical systems and turbulence, Lecture notes in mathemat­ics. Vol. 898 (pp. 366-381). Berlin: Springer.
  • Thelen, E. & Smith, L.B. (1994). A dynamic systems approach to the development of cognition and action. Cambridge, MA: The MIT Press.
  • Tschacher, W. & Dauwalder, J.P. (Eds.) (2003). The dynamical systems approach to cognition: Concepts and empirical paradigms based on self-organization, em­bodiment, and coordination dynamics. Singapore: World Scientific Publishing.
  • Van Orden, G.C., Holden, J.G., & Turvey, M.T. (2003). Self-organization of cogni­tive performance. Journal of Experimental Psychology: General, 132, 331-350.
  • Webber, C.L.Jr., Schmidt, M.A., & Walsh, J.M. (1995). Influence of isometric loading on biceps EMG dynamics as assessed by linear and nonlinear tools. Journal of Applied Physiology, 78, 814-822.
  • Webber, C.L.Jr. & Zbilut, J.P. (1994). Dynamical assessment of physiological systems and states using recurrence plot strategies. Journal of Applied Physiology, 76, 965-973.
  • Webber, C.L.Jr. & Zbilut, J.P. (2005). Recurrence quantification analysis of nonlinear dynamical systems. In M.A. Riley & G.C. Van Orden (Eds.), Tutorials in con­temporary nonlinear methods for the behavioral sciences (pp. 26-94). Retrieved June 1, 2012, from <http://www.nsf.gov/sbe/bcs/pac/nmbs/nmbs.jsp>
  • Zbilut, J.P. & Webber, C.L.Jr. (1992). Embeddings and delays as derived from quan­tification of recurrence plots. Physics Letters A, 171, 199-203.
  • Zbilut, J.P. & Webber, C.L.Jr. (2006). Recurrence quantification analysis. In M. Akay (Ed.), Wiley encyclopedia of biomedical engineering. Hoboken, NJ: John Wiley & Sons.
  • Zbilut, J.P., Sirabella, P., Giuliani, A., Manetti, C., Colosimo, A., & Webber, C.L.Jr. (2002). Review of nonlinear analysis of proteins through recurrence quantifica­tion. Cell Biochemistry and Biophysics, 36, 67-87.
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Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.doi-10_2478_v10057-012-0012-x
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