Language change in a multiple group society

Pop, Cristina-Maria; Frey, Erwin

doi:10.1103/physreve.88.022814

Cited by 5 publications

(7 citation statements)

References 39 publications

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“…is the set used to evaluate the performance of the classifier. A given example β can be characterized by a set of M features: 1) , F 2 = β (2) , . .…”

Section: Pattern Recognition Methodsmentioning

confidence: 99%

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Authorship recognition via fluctuation analysis of network topology and word intermittency

Amancio¹

2015

J. Stat. Mech.

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Abstract. Statistical methods have been widely employed in many practicalnatural language processing applications. More specifically, complex network concepts and methods from dynamical systems theory have been successfully applied to recognize stylistic patterns in written texts. Despite the large number of studies devoted to representing texts with physical models, only a few studies have assessed the relevance of attributes derived from the analysis of stylistic fluctuations. Because fluctuations represent a pivotal factor for characterizing a myriad of real systems, this study focused on the analysis of the properties of stylistic fluctuations in texts via topological analysis of complex networks and intermittency measurements. The results showed that different authors display distinct fluctuation patterns. In particular, it was found that it is possible to identify the authorship of books using the intermittency of specific words. Taken together, the results described here suggest that the patterns found in stylistic fluctuations could be used to analyze other related complex systems. Furthermore, the discovery of novel patterns related to textual stylistic fluctuations indicates that these patterns could be useful to improve the state of the art of many stylistic-based natural language processing tasks.

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“…is the set used to evaluate the performance of the classifier. A given example β can be characterized by a set of M features: 1) , F 2 = β (2) , . .…”

Section: Pattern Recognition Methodsmentioning

confidence: 99%

“…The application of concepts from physics in textual analysis has increasingly become widespread [1][2][3][4][5][6][7]. The use of entropy concepts is perhaps one of the most known examples of adapting methods from physics in language-based models [8].…”

Section: Introductionmentioning

confidence: 99%

Authorship recognition via fluctuation analysis of network topology and word intermittency

Amancio¹

2015

J. Stat. Mech.

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“…Social, as well as spatial heterogeneity may also be important. For example, it has been shown theoretically [94] that the time required for two social groups to reach linguistic consensus is highly sensitive to the level of affinity that individuals have for their own group.…”

Section: Interaction Networkmentioning

confidence: 99%

Spatial Evolution of Human Dialects

Burridge

2017

Phys. Rev. X

101

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The geographical pattern of human dialects is a result of history. Here, we formulate a simple spatial model of language change which shows that the final result of this historical evolution may, to some extent, be predictable. The model shows that the boundaries of language dialect regions are controlled by a length minimizing effect analogous to surface tension, mediated by variations in population density which can induce curvature, and by the shape of coastline or similar borders. The predictability of dialect regions arises because these effects will drive many complex, randomized early states toward one of a smaller number of stable final configurations. The model is able to reproduce observations and predictions of dialectologists. These include dialect continua, isogloss bundling, fanning, the wave-like spread of dialect features from cities, and the impact of human movement on the number of dialects that an area can support. The model also provides an analytical form for Séguy's Curve giving the relationship between geographical and linguistic distance, and a generalisation of the curve to account for the presence of a population centre. A simple modification allows us to analytically characterize the variation of language use by age in an area undergoing linguistic change.

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“…Finally, in [16] scaling law for the time needed to achieve consensus are obtained and numerically validated. This paper is one of the few considering parameter values outside the range in which the results of [12] are valid.…”

Section: Introductionmentioning

confidence: 99%

Continuous time limits of the utterance selection model

Michaud

2017

Phys. Rev. E

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This is the published version of a paper published in .Citation for the original published paper (version of record):Michaud, J. (2017) Continuous time limits of the utterance selection model. (2006)]. This is motivated by the fact that the Fokker-Planck continuous time limit derived in the original version of the USM is only valid for a small range of parameters. We investigate the consequences of relaxing these constraints on parameters. Using the normal approximation of the multinomial approximation, we derive a continuous time limit of the USM in the form of a weak-noise stochastic differential equation. We argue that this weak noise, not captured by the Kramers-Moyal expansion, cannot be neglected. We then propose a coarse-graining procedure, which takes the form of a stochastic version of the heterogeneous mean field approximation. This approximation groups the behavior of nodes of the same degree, reducing the complexity of the problem. With the help of this approximation, we study in detail two simple families of networks: the regular networks and the star-shaped networks. The analysis reveals and quantifies a finite-size effect of the dynamics. If we increase the size of the network by keeping all the other parameters constant, we transition from a state where conventions emerge to a state where no convention emerges. Furthermore, we show that the degree of a node acts as a time scale. For heterogeneous networks such as star-shaped networks, the time scale difference can become very large, leading to a noisier behavior of highly connected nodes. Phys

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Language change in a multiple group society

Cited by 5 publications

References 39 publications

Authorship recognition via fluctuation analysis of network topology and word intermittency

Authorship recognition via fluctuation analysis of network topology and word intermittency

Spatial Evolution of Human Dialects

Continuous time limits of the utterance selection model

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