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Language Dynamics
Language Dynamics
Our research work in Language Dynamics is supported by the Estonian Research Council, through the Grant PRG 1059, "Learning Processes in Language Dynamics".
Language dynamics employs complex systems models and tools to describe competition, evolution, and spreading of languages. We study mesoscopic ecological-like models of language competitions, as well as microscopic (possibly heterogeneous) many-agent models to study the spreading and evolution of languages.
On the top of this, we have also an interest and an active research line in language/dialect comparison and classification using statistical tools from complex data analysis.
We also studied the statistical properties of written text in relation to the appearance of power-laws, e.g. the Zipf's law.
Chek the publications below for further details.
PUBLICATIONS
Learning thresholds lead to stable language coexistence,
Mikhail V. Tamm, Els Heinsalu, Stefano Scialla, Marco Patriarca,
submitted, arXiv:2406.14522Language dynamics model with finite-range interactions influencing the diffusion of linguistic traits and human dispersal
Clément Zankoc; Els Heinsalu; Marco Patriarca
European Physical Journal B 97, 66 (2024)
https://doi.org/10.1140/epjb/s10051-024-00706-3A three-state language competition model including language learning and attrition,
Stefano Scialla, Jens-Kristjan Liivand, Marco Patriarca, Els Heinsalu,
Front. Complex Syst. 1-1266733 (2023),
https://doi.org/10.3389/fcpxs.2023.1266733The Physics of Languages
Marco Patriarca, Els Heinsalu, and David Sánchez
Physics World, 13 June 2023
https://physicsworld.com/a/the-physics-of-languages/The role of bilinguals in the Bayesian naming game,
Gionni Marchetti, Marco Patriarca, Els Heinsalu.
Physica D 428, 133062 (2021) doi:10.1016/j.physd.2021.133062 arXiv:2106.00069A Bayesian Approach to the Naming Game Model,
Gionni Marchetti, Marco Patriarca, and Els Heinsalu,
Frontiers in Physics 8, 10 (2020) doi:10.3389/fphy.2020.00010 arXiv:1911.13012"Languages in Space and Time: Models and Methods from Complex Systems Theory",
Patriarca, Marco; Heinsalu, Els; Leonard, Jean Leó.
Cambridge University Press (2020).A Bird’s-Eye View of Naming Game Dynamics: From Trait Competition to Bayesian Inference,
Gionni Marchetti, Marco Patriarca, and Els Heinsalu,
Chaos 30, 063119 (2020) doi:10.1063/5.0009569 arXiv:2004.01994Patterns of linguistic diffusion in space and time: The case of Mazatec,
J.L. Léonard, M. Patriarca, E. Heinsalu, K. Sharma, A Chakraborti.
in: "Complexity Applications in Language and Communication Sciences",
À, Massip-Bonet, G. Bel-Enguix, A. Bastardas-Boada, Editors,
p. 139-170 Springer (2019) doi:10.1007/978-3-030-04598-2_9Applicazioni alla linguistica dei metodi e modelli della teoria dei sistemi complessi,
Marco Patriarca, Els Heinsalu, Jean Léo Léonard,
p. 103-143, Il Calamo (2018).
in: "Mutamento Linguistico e Biodiversità"
(Atti del XLI Convegno della Società Italiana di Glottologia, Perugia, 1-3 dicembre 2016)
L. Costamagna, E. Di Domenico, A. Marcaccio, S. Scaglione, and B. Turchetta, editors,
II Calamo, Roma, 2018. ISBN: 9788898640317The role of bilinguals in language competition
E Heinsalu, M Patriarca, JL Léonard
Advances in Complex Systems 17 (01), 1450003 37 2014M. Patriarca, X. Castelló, J.R. Uriarte, V.M. Eguı́luz, and M. San Miguel
Modeling two-language competition dynamics
Advances in Complex Systems 15 (2012) 1250048
doi:10.1142/S0219525912500488 arXiv:1206.2960M. Patriarca and E. Heinsalu
Influence of geography on language competition
Physica A 388 (2009) 174 doi:10.1016/j.physa.2008.09.034 arxiv.org:0807.3100M. Patriarca and T. Leppänen
Modelling language competition
Physica A 338 (2004) 296
doi:10.1016/j.physa.2004.02.056
Resonances in cell-networks
Resonances in cell-networks
The function and properties of biological cell networks depends on their global dynamical properties. Indeed, the very reason for the existence of cell networks is that they have special features that single cells don't have. We investigate various types of cell networks and the resonances appearing in their collective behaviors.
In our last paper "Diversity-induced decoherence" we study a network of coupled oscillators with a strong time scale separation uncovering a new nontrivial effect that we name diversity-induced decoherence (DIDC), in which heterogeneity modulates the mechanism of self-induced stochastic resonance to inhibit the coherence of oscillations.
We have studied also mathematical models β-cell networks, showing that the emergence of pacemakers (or hubs) in the system is a natural consequence of the oscillator population diversity. We have also studied the interplay of noise and disorder in cell networks, showing that it presents a wide range of effects, which can be synergistic or independent of each other.
PUBLICATIONS
Diversity-induced decoherence
Marius E. Yamakou, Els Heinsalu, Marco Patriarca, and Stefano Scialla,
Phys. Rev. E 106, L032401 (2022)
doi: 10.1103/PhysRevE.106.L032401 https://arxiv.org/abs/2206.08064The interplay between diversity and noise in an excitable cell network model,
Stefano Scialla, Marco Patriarca, Els Heinsalu.
Europhysics Letters 137, 51001 (2022) doi: 10.1209/0295-5075/ac5cdb arXiv:2203.12506Hubs, diversity, and synchronization in FitzHugh-Nagumo oscillator networks: Resonance effects and biophysical implications,
Stefano Scialla, Alessandro Loppini, Marco Patriarca, and Els Heinsalu.
Phys. Rev. E 103, 052211 (2021) doi:10.1103/PhysRevE.103.052211 arXiv:2105.05652
Heterogeneity and diffusion in Ecological Competition
Heterogeneity and diffusion in Ecological Competition
Competition models are a fundamental paradigm in complex systems for the study of natural selection in different processes, from ecological competition to cultural diffusion and epidemic spreading.
The interplay between diffusion and competition is known to lead to relevant phenomena such as the appearance of wave fronts.
In our research we take into account two other crucial features of ecological systems.
First, we consider the finite-range character of interactions,. In this case the system can develop patterns (in the form of clumped distributions).
Furthermore, we include heterogenity in the diffusion properties of the individuals. We find that the natural selection process can proceed in a very different way and, in principle, any individual, either slow or fast, can win the competition process, depending on the system parameters.
PUBLICATIONS
Influence of invasion on natural selection in dispersal-structured populations,
David Navidad Maeso, Marco Patriarca, Els Heinsalu,
Physica A 547, 124427 (2022),
doi: 0.1016/j.physa.2022.127389 arxiv.org/abs/2204.11899The dynamics of natural selection in dispersal-structured populations,
Heinsalu, Els; Navidad Maeso, David; Patriarca, Marco,
Physica A 547 (2020) 124427 doi:0.1016/j.physa.2020.124427 arXiv:2004.14689The role of dispersal in competition success and in the emerging diversity,
Els Heinsalu, David Navidad Maeso, and Marco Patriarca,
Eur. Phys. J. B 91, 255 (2018) doi:10.1140/epjb/e2018-90372-5 arXiv:2004.06088
Power-Law distributions in Economics and Text Analysis
Power-Law distributions in Economics and Text Analysis
Power-law distributions are ubiquitous in many systems, from the Zipf's law in text analysis to the Pareto law found in wealth distributions.
We have studied microscopic models that leads to the spontaneous emergence of power-law distribution, as a consequence of the diversity of the constituent units. Thus, a possible interpretation of the appearance of power-laws is that it is dynamically originated from the heterogeneity of the system.
PUBLICATIONS
In: "Econophysics and Sociophysics: Recent Progress and Future Directions", Frédéric Abergel & al. Editors, Springer (2017) ISSN 2039-411X:
Kinetic Exchange Models as D Dimensional Systems: A Comparison of Different Approaches (p.147), Marco Patriarca, Els Heinsalu, Amrita Singh, and Anirban Chakraborti.
The Microscopic Origin of the Pareto Law and Other Power-Law Distributions (p. 159), Marco Patriarca, Els Heinsalu, Anirban Chakraborti, and Kimmo Kaski.
Power-laws as statistical mixtures
M Patriarca, E Heinsalu, L Marzola, A Chakraborti, K Kaski
Proceedings of ECCS 2014: European Conference on Complex Systems, 271-282 (2016)M. Patriarca, A. Chakraborti, K. Kaski, and G. Germano
Kinetic theory models for the distribution of wealth: power law from overlap of exponentials
in: Econophysics of Wealth Distributions, Econophys-Kolkata 1, A. Chatterjee, S.Yarlagadda, B.K. Chakrabarti, Eds., Springer, 2005
doi:10.1007/88-470-0389-X 10 arXiv:physics/0504153
Kinetic models of wealth exchange
Kinetic models of wealth exchange
The full shape of wealth distribution from small to large values of wealth has always represented a challenge for economic modelers. Even if already suggested by Benoit Mandelbrot in 1960, the analogy between economic exchanges (of wealth between economic agents) and energy exchange (between e.g. molecules of a fluid) was fully appreciated and worked out only starting at the end of the 90's. There is now a solid research line in this topic and correspondingly a whole family of kinetic wealth exchange models that can take into account various features of a system (such as saving propensity/productivity, taxation, loans, behavioral traits, etc.) that produce wealth distributions in excellent agreement with real data.
PUBLICATIONS
Uni-vs. bi-directional kinetic exchange models
E Heinsalu, M Patriarca
International Journal of Computational Economics and Econometrics 5 (3), 213-219 3, 2015Kinetic models of immediate exchange
E Heinsalu, M Patriarca
The European Physical Journal B 87, 1-10, 28, 2014Kinetic exchange models: From molecular physics to social science
M Patriarca, A Chakraborti
American Journal of Physics 81 (8), 618-623 (2013)A. Chakraborti, I.M. Toke, M. Patriarca, and F. Abergel
Econophysics review: II. Agent-based models
Quantitative Finance 11 (2011) 1013-1041
doi:10.1080/14697688.2010.539249 arXiv:0909.1974A. Chakraborti, I.M. Toke, M. Patriarca, and F. Abergel
Econophysics review: I. Empirical facts
Quantitative Finance 11 (2011) 991-1012 doi:10.1080/14697688.2010.539248 arXiv:0909.1974M. Patriarca, E. Heinsalu and A. Chakraborti
Basic kinetic wealth-exchange models: common features and open problems
Eur. Phys. J. B 73, (2010) 145 doi:10.1140/epjb/e2009-00418-6 arXiv:physics/06112452A. Chakraborti and M. Patriarca
A variational principle for the Pareto power law
Phys. Rev. Lett. 103 (2009) 228701 doi:10.1103/PhysRevLett.103.228701 arXiv:cond-mat/0605325A. Chakraborty and M. Patriarca
Gamma-distribution and Income inequality
Pramana J. Phys. 71(2) (2008) 233
Special Issue: Statistical Physics Approaches to Multidisciplinary Problems
doi:10.1007/s12043-008-0156-3 arXiv.org:0802.4410 http://www.ias.ac.in/pramana/v71/p233/fulltext.pdfM. Patriarca, A. Chakraborti, and G. Germano
Influence of saving propensity on the power-law tail of wealth distribution
Physica A 369 (2006) 723
doi:10.1016/j.physa.2006.01.091 arXiv:physics/0506028M. Patriarca, A. Chakraborti, K. Kaski, and G. Germano
Kinetic theory models for the distribution of wealth: power law from overlap of exponentials
in: Econophysics of Wealth Distributions, Econophys-Kolkata 1, A. Chatterjee, S.Yarlagadda, B.K. Chakrabarti, Eds., Springer, 2005
doi:10.1007/88-470-0389-X 10 arXiv:physics/0504153M. Patriarca, A. Chakraborti, and K. Kaski
A statistical model with a standard Γ-distribution
Phys. Rev. E 70, (2004) 016104
doi:10.1103/PhysRevE.70.016104 arXiv:cond-mat/0402200M. Patriarca, A. Chakraborti, and K. Kaski
Gibb’s versus non-Gibb’s distributions in money dynamics
Physica A 340 (2004) 334
doi:10.1016/j.physa.2004.04.024 arXiv:cond-mat/0312167
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