Human languages are not static entities. Linguistic conventions, whose social and communicative meaning are understood by all members of a speech community, are gradually altered or replaced, whether by changing their forms, meanings, or by the loss of or introduction of altogether new distinctions. How do large speech communities go about re-negotiating arbitrary associations in the absence of centralised coordination? This thesis first provides an overview of the plethora of explanations that have been given for language change. Approaching language change in a quantitative and evolutionary framework, mathematical and computational modelling is put forward as a tool to investigate and compare these different accounts and their purported underlying mechanisms in a rigorous fashion. The central part of the thesis investigates a relatively recent addition to the pool of mechanisms that have been proposed to influence language change: I will compare previous accounts with a momentum-based selection account of language change, a replicator-neutral model where the popularity of a variant is modulated by its momentum, i.e. its change in frequency of use in the recent past. I will discuss results from a multi-agent model which show that the dynamics of a trend-amplifying mechanism like this are characteristic of language change, in particular by exhibiting spontaneously generated s-shaped transitions. I will also discuss several empirical predictions made by a momentum-based selection account which contrast with those that can be derived from other accounts of language change. Going beyond theoretical arguments for the role of trends in language change, I will go on to present fieldwork data of speakers’ awareness of ongoing syntactic changes in the Shetland dialect of Scots. Data collected using a novel questionnaire methodology show that individuals possess explicit knowledge about the direction as well as current progression of ongoing changes, even for grammatical structures which are very low in frequency. These results complement previous experimental evidence which showed that individuals both possess and make use of implicit knowledge about age-dependent usage differences during ongoing sound changes. Echoing the literature on evolutionary approaches to language change, the final part of the thesis stresses the importance of explicitly situating different pressures either in the domain of the innovation of new or else the selection of existing variants. Based on a modification of the Wright-Fisher model from population genetics, I will argue that trend-amplification selection mechanisms provide predictions that neatly match empirical facts, both in terms of the diachronic dynamics of language change, as well as in terms of the synchronic distribution of linguistic traits that we find in the world.

L’objectif de ce travail de thèse est de développer une méthodologie d’extraction de connaissances à partir de brevets pour aider les concepteurs dans la phase de résolution de problèmes industriels. La méthodologie est fondée sur trois piliers : la définition, la recherche / analyse et l’innovation. La définition exhaustive de la fonction principale du système industriel cible le champ de recherche et permet la récupération de mots clés initiaux grâce à une analyse approfondie de l’existant. La recherche itérative des brevets se base sur la décomposition fonctionnelle et sur l’analyse physique. L’analyse intègre la décomposition fonctionnelle énergétique pour déceler les énergies, les flux fonctionnels transmis et les phénomènes physiques impliqués dans le processus de conversion énergétique afin de sélectionner des effets physiques potentiellement pertinents. Pour délimiter le champ d’exploration nous formulons des requêtes de recherche à partir d’une base de données de mots clés constituée par des mots clés initiaux, des mots clés physiques et des mots clés technologiques. Une matrice des découvertes basée sur les croisements entre ces mots clés permet le classement des brevets pertinents. La recherche des opportunités d’innovation exploite la matrice des découvertes pour déceler les tendances évolutives suivies par les inventions. Les opportunités sont déduites à partir de l’analyse des cellules non pourvues de la matrice des découvertes, de l’analyse par tendances d’évolution et du changement de concept par la substitution du convertisseur énergétique. Nous proposons des tendances d’évolution construites à partir de lois d’évolution de la théorie TRIZ, d’heuristiques de conception et de règles de l’art de l’ingénieur. Un cas d’application concernant l’étude d’évolution et la proposition de nouveaux systèmes de séparation de mélanges bi-phasiques en offshore profond met en valeur la méthode. / The aim of this thesis work is the development of a methodology for knowledge extraction from patents to assist design engineers in the industrial problem-solving phase. The methodology is based on three pillars: definition, search / analysis and innovation. A comprehensive definition of the main function of the industrial system delimits the research field and allows the retrieval of initial keywords through a detailed analysis of what is currently available. The iterative patent search is based on functional decomposition and physical analysis. The analysis phase uses energy functional decomposition to identify energies, transmitted functional flows and physical phenomena involved in the energy conversion process in order to select potentially relevant physical effects. To delineate the exploration field we formulate search queries from a keywords database composed by initial, physical, and technological keywords. A discovery matrix based on the intersections between these keywords allows the classification of pertinent patents. The research for innovation opportunities exploits the discovery matrix in order to decipher the evolutionary trends followed by inventions. Opportunities are deduced from an analysis of the discovery matrix empty cells, an analysis of the evolution trends, and from changing the concept by energy converter substitution. We propose evolution trends constructed from the evolution laws of TRIZ theory, design heuristics, and rules of the art of the engineering. An application case concerning the study of the evolution and the proposal of innovative biphasic separation systems in deep offshore highlights the method.