Conference Agenda

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Session Overview
Panel: Agent-based Modelling In Historical Sociolinguistics (1/2)
Wednesday, 31/May/2023:
11:30am - 1:00pm

Session Chair: Peter Dekker
Session Chair: Dirk Pijpops
Session Chair: Bart de Boer
Location: Room 'Magritte'

Session Abstract

An important problem in historical sociolinguistics is the actuation problem (Weinreich et al., 1968): why does a certain instance of language change take place in a specific language, in a specific social group, and not elsewhere? To investigate this type of question, several types of methods could be used, including corpus studies (Raumolin-Brunberg & Nevalainen, 2007; Rutten & Van der Wal, 2014), quantitative cross-linguistic studies (Ladd et al., 2015) and laboratory experiments. In this workshop, we propose agent-based models, computer simulations of interactions between speakers, as a method to study the conditions under which language change takes place. Agent-based models allow for testing of hypotheses which involve factors that are not easy to manipulate in the real world. Relatively abstract agent-based models have been used to study language evolution (e.g. Dale & Lupyan, 2012), but for the questions addressed by historical sociolinguistics, the strength of agent-based models is to combine them with real data and use them for real-world case studies. Usually, no large amounts of data are needed for agent-based models: the data often serve to initialise the model and/or to evaluate the model outcomes. This makes agent-based models suitable to study hypotheses about language change from below (Elspaß et al., 2007; Auer et al., 2015), using historical material of informal language use, which may be less widely available. All in all, agent-based models allow to study how supposedly universal mechanisms behind language change have different outcomes in different languages and social settings.

Auer, A., Peersman, C., Pickl, S., Rutten, G., & Vosters, R. (2015). Historical sociolinguistics: The field and its future. Journal of Historical Sociolinguistics, 1(1), 1–12.

Dale, R., & Lupyan, G. (2012). Understanding the origins of morphological diversity: The linguistic niche hypothesis. Advances in Complex Systems, 15(03n04), 1150017.

Elspaß, S., Langer, N., Scharloth, J., & Vandenbussche, W. (Eds.). (2007). Germanic Language Histories ‘from Below’ (1700-2000) (Studia Linguistica Germanica 86). Walter de Gruyter, Berlin/New York.

Raumolin-Brunberg, H., & Nevalainen, T. (2007). Historical sociolinguistics: The corpus of early english correspondence. In J. C. Beal, K. P. Corrigan, & H. L. Moisl (Eds.), Creating and digitizing language corpora: Volume 2: Diachronic Databases (pp. 148–171). Palgrave Macmillan UK.

Rutten, G., & Van der Wal, M. J. (2014). Letters as loot: A sociolinguistic approach to seventeenth-and eighteenth-century Dutch (Vol. 2). John Benjamins Publishing Company.

Ladd, D. R., Roberts, S. G., & Dediu, D. (2015). Correlational Studies in Typological and Historical Linguistics. Annual Review of Linguistics, 1(1), 221–241.

Weinreich, U., Labov, W., & Herzog, M. I. (1968). Empirical foundations for a theory of language change. WP Lehmann-Y. Malkiel (Hrsgg.), Directions for Historical Linguistics, Austin/London.

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11:30am - 12:00pm

Panel introduction

Peter Dekker1, Dirk Pijpops2, Bart de Boer1

1Vrije Universiteit Brussel, Belgium; 2Université de Liège, Belgium

In the Introduction session of this workshop, we will give a general overview of the use of agent-based models in historical sociolinguistics, by discussing how to construct a model given a research question, what are different paradigms that exist within agent-based modelling and which sociolinguistic data can be integrated.

12:00pm - 12:30pm

The Best Solution Short of Time Travel: Simulating Sociolinguistic Theories Around Why Belgian Standard Dutch Pronunciation Did Not Follow Netherlandic Innovations

Anthe Sevenants

Katholieke Universiteit Leuven, Belgium

Around 1930, the Standard Dutch pronunciation in the Netherlands sounded remarkably similar to the Standard Dutch still spoken today in Belgium. Interestingly, the two standards were aligned at one point, but after 1930, the Dutch standard started to shift away (H. Van de Velde 1996). The most notable aspects of this shift were, among others, the diphthongisation of the [e] and [o] sounds towards [ei] and [oʊ] and the devoicing of syllable-initial fricatives. Speakers in Belgium did not follow this shift, which led to the divergence we see today. There have been several attempts to explain this divergence on the basis of social factors: (i) there was not enough contact between the two countries (van den Toorn 1997) (ii) the Dutch standard evolved too fast, and Belgian speakers could not follow its pace (F. Van de Velde 2019) (iii) Belgian speakers did not want to sound like the Dutch (‘ethnocentrism’, Deprez 1985) (iv) a difference in language norms in Dutch and Belgian public broadcasting companies (H. Van de Velde 1996) accelerated change in The Netherlands and inhibited change in Belgium. Since there is very little data available – and we cannot go back in time to collect evidence – it is difficult to investigate these sociolinguistic tendencies in a historical context. Therefore, the theories are examined using an agent-based simulation model. The results show that a lack of contact between both countries can indeed lead to divergence in the model, but only if abroad travel is at least 5000 times less likely than domestic travel. The pace of language change in the Netherlands does not have a sizeable impact on convergence or divergence tendencies in Belgium in the model. High values for ethnocentrism in Belgian agents are able to lead to divergence in the model, as long as these high values are shared by the entire population. Media receptiveness (assumed to be a powerful force in this model) in agents always kickstarts convergence in the model and it accelerates this convergence as well.


Deprez, Kas. 1985. ‘De aard van het Nederlands in Vlaanderen’. Heibel: onafhankelijk kritisch-satirisch-polemisch tijdschrift 19 (4): 101–27.

Toorn, Maarten Cornelis van den. 1997. Geschiedenis van de Nederlandse taal. Amsterdam: university press.

Van de Velde, Freek. 2019. ‘External History of Dutch’. Lecture, Leuven, May 8.

Van de Velde, Hans. 1996. Variatie En Verandering in Het Gesproken Standaard-Nederlands (1935-1993).

12:30pm - 1:00pm

How Demography Affects the Use of Strong and Weak Past Tense Forms in English, Dutch and German. Evidence from Agent-based Simulation, and Historical Linguistic and Demographic Data.

Dirk Pijpops1, Isabeau De Smet2, Julie Nijs2, Freek Van de Velde2

1Université de Liège, Belgium; 2Katholieke Universiteit Leuven, Belgium

One of the best-known long-term changes in the Germanic languages is the rise of the weak past tense (e.g. kick ~ kicked) at the expense of the strong past tense (e.g. sing ~ sang). This change has been progressing at different speeds in various languages, with the strong inflection having declined more in English than in Dutch or German, for instance. We propose that such differences can be explained in part through demographic developments, namely migration and urbanization (compare Lupyan and Dale 2010; Dale and Lupyan 2012: Bentz and Winter 2013, although see Cuskley et al. 2015; De Smet et al. 2022). We begin by investigating the behavior of an agent-based simulation that implements both inflections as competitors, with the strong inflection initially dominant in terms of frequency, and still consisting of several regular ablaut classes. Its crucial distinction with the weak inflection in the simulation only lies in the weak inflection’s general applicability, i.e. the ability of the weak inflection to form past tense forms for any verb, in principle. The simulation predicts that an influx of new agents indeed drives up the success of the weak inflection: the greater the demographic upheaval, the stronger the surge of the weak inflection.

Next, we test this prediction with empirical data about historical language changes and demography. In particular, data from English and German are taken respectively from Lieberman et al. (2007) and Cuskley et al. (2014), and we replicate these studies for Dutch. These data are then cross tabulated with historical urbanization rates from Bairoch et al. (1988). It is found that (i) both urbanization and weakening rates are highest in English, followed by Dutch and German, and (ii) English urbanization best predicts English weakening, Dutch urbanization best predicts Dutch weakening, and German urbanization best predicts German weakening.

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