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According to usage-based linguistics, language variation addresses a functional need of the language user. That functional need may be dependent on the lexical realization of the varying constructions. For instance, while it may be useful to have an argument structure alternation express a particular semantic distinction for particular verbs or themes, that same distinction may be less relevant for other verbs or themes. As such, it has been argued that language variation should be investigated at low levels of schematicity, e.g. by studying argument structure alternations separately for various verbs, themes, etc. In this paper, we develop a data-driven procedure to do so, based on Memory-based Learning (MBL). The procedure focusses on generating hypotheses, is scalable, and can work with small datasets. It consists of three steps: (i) choosing features for the MBL classifier, (ii) running MBL analyses and selecting which analyses to put under further scrutiny, and (iii) inspecting which features were most useful in predicting the choice of variant in these analyses. Finally, the hypotheses that are inferred from these features are put to the test on separate data. As an example study, we investigate the Dutch naar-alternation.

While the Netherlandic standard Dutch pronunciation norm around 1930 was still very much like the Belgian norm, it shifted considerably in the course of the 20th century (Van de Velde 1996, Van de Velde et al. 2010). In Belgium, no such evolution occurred, which caused the pronunciation of both language varieties to diverge. As of yet, there is no conclusive evidence as to why this divergence has happened. Because there is not enough data to investigate the divergence empirically, it is examined using an agent-based simulation model in Python. Though we cannot ‘prove’ that the mechanisms described in the theories from the literature actually happened in reality, we can test their plausibility by checking whether the effects described in the theories also appear in our model which attempts to mimic real-world circumstances. Four research questions based on theories found in the literature are tested: 1. Can a reduced contact between speakers from the Netherlands and Belgium result in a divergence between the standard pronunciations of both countries in the model? 2. Can an increased pace of language change in Dutch speakers cause a divergence between the standard pronunciations of the Netherlands and Belgium in the model? 3. Can we relate increased ethnocentrism in Belgian speakers to less adoption of Netherlandic innovations or even divergence in the model? 4. Can an increased media influence amplify the existing tendencies for language change (acceleration or inhibition) in Belgium in the 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. If ethnocentrism decreases along with how close agents live to the border, it has little effect. Media receptiveness in agents always kickstarts convergence in the model and it accelerates this convergence as well. Since media influence is implemented as a powerful force in the simulation, this result must be interpreted from the viewpoint of media having a sizeable impact on language change. ispartof: Computational Linguistics in the Netherlands Journal vol:11 pages:5-26 status: Published online

no ISSN/ISBN ispartof: pages:45-48 ispartof: Collated Papers for the ALTE 7th International Conference, Madrid pages:45-48 ispartof: ALTE 7th International Conference location:Madrid status: Published online

geen doi ispartof: Levende Talen Tijdschrift vol:22 issue:1 pages:3-13 status: published

ispartof: Tijdschrift voor Hoger Onderwijs vol:39 issue:1 pages:39-54 status: Published online

This paper introduces snelSLiM, a corpus linguistics tool to perform keyword analysis using Stable Lexical Marker Analysis. SLMA goes beyond regular keyword analysis by assuring stability across the documents within a corpus and can be used with a contrastive or specific reference corpus as well as a general reference corpus. With snelSLiM, it is easy to perform SLMA as well as explore the resulting keywords through a user-friendly web interface. Great performance, support for many corpus formats, collocational analysis of keywords and visualizations make it an attractive tool for initial exploration of new corpora. A demo version is available on http://demo.snelslim.org/

ispartof: Nederlandse Taalkunde vol:25 issue:1 pages:101-123 status: published

ispartof: Cognitive Contact Linguistics. Placing Usage, Meaning and Mind at the Core of Contact-Induced Variation and Change pages:213-250 ispartof: Cognitive Linguistics Research vol:62 pages:213-250 status: published

The present study examined the effects of written comprehensive corrective feedback forms on learners’ cognitive load, immediate grammatical accuracy, L2 development, and attitudinal engagement. A total of 139 low intermediate EFL university writers were randomly assigned to four experimental conditions (direct correction on grammatical errors; metalinguistic correction on grammatical errors; direct correction on all surface-level errors; metalinguistic correction on all surface-level errors) and a control group (self-correction). Learners wrote four texts, completed a mental-effort scale, and answered a questionnaire of attitudinal engagement. Mixed-model analyses revealed that direct correction on grammatical errors imposed the lowest cognitive load, brought about the most immediate grammatical accuracy (during text revision), and yielded the most L2 development (four weeks after the treatment). Also, a statistically significant attitudinal difference was found between learners receiving direct correction on all surface-level errors and their metalinguistic counterpart. Theoretical and pedagogical implications are discussed. ispartof: Language Learning vol:68 issue:3 pages:813-850 status: published

In this study, we investigate which factors influence the linguistic distance of Catalan dialectal pronunciations from standard Catalan. We use pronunciations from three regions where the northwestern variety of the Catalan language is spoken (Catalonia, Aragon and Andorra). In contrast to Aragon, Catalan has an official status in both Catalonia and Andorra, which likely influences standardization. Because we are interested in the potentially large range of differences that standardization might promote, we examine 357 words in Catalan varieties and in particular their pronunciation distances with respect to the standard. In order to be sensitive to differences among the words, we fit a generalized additive mixed-effects regression model to this data. This allows us to examine simultaneously the general (i.e. aggregate) patterns in pronunciation distance and to detect those words that diverge substantially from the general pattern. The results reveal higher pronunciation distances from standard Catalan in Aragon than in the other regions. Furthermore, speakers in Catalonia and Andorra, but not in Aragon, show a clear standardization pattern, with younger speakers having dialectal pronunciations closer to the standard than older speakers. This clearly indicates the presence of a border effect within a single country with respect to word pronunciation distances. Since a great deal of scholarship focuses on single segment changes, we compare our analysis to the analysis of three segment changes that have been discussed in the literature on Catalan. This comparison shows that the pattern observed at the word pronunciation level is supported by two of the three cases examined. As not all individual cases conform to the general pattern, the aggregate approach is necessary to detect global standardization patterns.

Distributional semantic models have shown to be a successful technique for Word Sense Disambiguation and Word Sense Induction tasks. However, these models, and more specifically the token-level variants, are extremely parameter-rich. We are still in the dark on how the different parameters can be efficiently set and even more on how to evaluate the outcome when no gold standard is readily available. To gain a better insight, we are developing a visual analytics approach which shows these models in two ways: a scatterplot matrix for inter-model parameter comparison and zoomable individual scatter plots allowing for more details on-demand. More specifically, we first use a scatterplot matrix to compare models with different parameter settings in a single view. This enables us to track selections of tokens over different models. On top of this, we create a scatter plot for each individual model, enriched with both model dependent and model independent features. This way, we can have a more in-depth visual analysis of what is going on and visualise the distinct properties or parameters of the individual model. ispartof: pages:24-29 ispartof: Proceedings of the LREC 2016 Workshop: VisLR II: Visualization as Added Value in the Development, Use and Evaluation of Language Resources pages:24-29 ispartof: VISLR location:Portorož, Slovenia date:23 May - 23 May 2016 status: published

In this contribution, we will focus on the lectal conditioning of lexical collocations. First, we will analyze how register and national variety modify the distributional properties of AN collocations in Dutch. Next, we will analyze how those lectal variables alter the impact of lexical collocations on the alternation between two inflectional variants of the adjective in Dutch definite NPs with a singular neuter head noun. no isbn ispartof: pages:89-92 ispartof: Proceedings of the 5th Conference on Quantitative Investigations in Theoretical Linguistics pages:89-92 ispartof: Quantitative Investigations in Theoretical Linguistics location:Leuven date:12 Sep - 14 Sep 2013 status: published

This paper presents a corpus study of the alternation between the reflexive and transitive argument constructions of the Dutch psych verbs ergeren (‘to annoy’), interesseren (‘to interest’), storen (‘to disturb’) and verbazen (‘to amaze’), as in Jij ergert je aan mij vs. Ik erger jou (both ‘I annoy you’). Logistic regression analysis revealed that the choice of the language user was driven by – in order of decreasing importance – the choice of verb, the morphological form of the stimulus, the animacy of the stimulus, the morphological form of the experiencer, and a number of nuisance variables. However, verbs whose lexical meaning entailed a more agentive experiencer did not more often realize this experiencer in subject position than other verbs, nor could the preference of the verbs be predicted by looking at their etymology. ispartof: pages:5-5 ispartof: Proceedings of the 6th Conference on Quantitative Investigations in Theoretical Linguistics pages:5-5 ispartof: Quantitative Investigations in Theoretical Linguistics location:Tuebingen date:4 Nov - 6 Nov 2015 status: published

ispartof: pages:1-5 ispartof: Proceedings of the 6th Conference on Quantitative Investigations in Theoretical Linguistics pages:1-5 ispartof: Quantitative Investigations in Theoretical Linguistics (QITL) location:Tübingen, Germany date:4 Nov - 6 Nov 2015 status: published

no issn ispartof: pages:67-78 ispartof: Actes de JADT 2014 pages:67-78 ispartof: Journées internationales d’analyse statistique des données textuelles (JADT) location:Paris date:3 Jun - 6 Jun 2014 status: published

ispartof: pages:252-265 ispartof: Actes des Ateliers TALN 2014 pages:252-265 ispartof: Traitement Automatique des Langues Naturelles (TALN) location:Marseille date:1 Jul - 4 Jul 2014 status: published

ispartof: Corpus Methods for Semantics: Quantitative studies in polysemy and synonymy pages:487-533 ispartof: Human Cognitive Processing vol:43 pages:487-533 status: published

Although the aggregation of many linguistic variables has provided new insights into the structure of language varieties, aggregation studies have been criticized for obscuring the behavior of individual input variables. Previous solutions to this criticism consisted of extensive post-hoc calculations, simple correlation measures, or highly complex algorithms. We think that these solutions can be improved. Therefore, the current article proposes a creative use of Individual Differences Scaling (INDSCAL) as an alternative, more straightforward solution. INDSCAL is a branch of Multidimensional Scaling, which is currently the preferred dimension reduction technique for most aggregation studies. The link to the existing methodology and the simplicity of its rationale are the main advantages of INDSCAL. The article introduces INDSCAL by means of a non-linguistic example, a discussion of the mathematical properties, and a case study on the lexical convergence between Belgian and Netherlandic Dutch in a corpus of language from 1950 and 1990. The case study shows how INDSCAL reproduces the results of a typical aggregation study, but elegantly keeps open the possibility of investigating the behavior of individual variables. © The Author 2013. Published by Oxford University Press on behalf of ALLC. All rights reserved. ispartof: Literary and Linguistic Computing vol:29 issue:1 pages:89-106 status: published

Within Computational Linguistics, distributional models of semantics have become the mainstay of large-scale modelling of lexical semantics. Distributional modelling also holds a large potential for research in Linguistics proper : It allows linguists to base their analysis on large amounts of usage data, thus vastly extending their empirical basis, and makes it possible to detect potentially interesting semantic patterns. However, so far, there have been relatively few applications, mainly because of the technical complexity and the lack of a linguist-friendly interface to explore the output. In this paper, we propose an interactive visualization of a distributional similarity matrix based on Multi-Dimensional Scaling. We present our prototype for a visualization tool built in Processing which opens up new possibilities for the visual analysis of token-based models and apply it to a small case study of a Dutch polysemous word. ispartof: pages:154-166 ispartof: Actes de SemDis 2013 : Enjeux actuels de la sémantique distributionnelle pages:154-166 ispartof: Traitement Automatique du Langage Naturel location:Les Sables-d'Olonne date:17 Jun - 21 Jun 2013 status: published

Corpus linguistic research relies on corpora which generally display an unbalanced structure. We will discuss a potential corollary of this biased structure which is rarely accounted for in (corpus) linguistics, namely con-founding variables. These are variables increasing, diminishing or reversing an explanatory variables marginal effect compared to its conditional effect. Analyzing four instances of confounding in a variational case study governed by a series of categorical explanatory variables, we will argue that these latent confounders can be unveiled modeling the co-occurrence patterns of the explanatory variables by means of a multiple correspondence analysis. ispartof: pages:923-936 ispartof: Proceedings of the 11th International Conference on the Statistical Analysis of Textual Data pages:923-936 ispartof: International Conference on the Statistical Analysis of Textual Data location:Liège date:11 Jun - 13 Jun 2012 status: published

In statistical NLP, Semantic Vector Spaces (SVS) are the standard technique for the automatic modeling of lexical semantics. However, it is largely unclear how these black-box techniques exactly capture word meaning. To explore the way an SVS structures the individual occurrences of words, we use a non-parametric MDS solution of a token-by-token similarity matrix. The MDS solution is visualized in an interactive plot with the Google Chart Tools. As a case study, we look at the occurrences of 476 Dutch nouns grouped in 214 synsets. ispartof: pages:16-24 ispartof: Proceedings of the EACL-2012 joint workshop of LINGVIS & UNCLH: Visualization of Language Patters and Uncovering Language History from Multilingual Resources pages:16-24 ispartof: European Chapter of the Association for Computational Linguistics location:Avignon date:23 Apr - 27 Apr 2012 status: published

ispartof: pages:883-895 ispartof: Proceedings of the 11th International Conference on Textual Data Statistical Analysis pages:883-895 ispartof: International Conference on Textual Data Statistical Analysis location:Liège, Belgium date:13 Jun - 15 Jun 2012 status: published

ispartof: Pluricentric Languages: Linguistic Variation and Sociognitive Dimensions. pages:541-554 ispartof: pages:541-554 ispartof: International Conference on Pluricentric Languages location:Braga, Portugal date:15 Sep - 17 Sep 2010 status: published

This paper describes how a toolset developed for the purposes of variational linguistics to identify regional variants, can be used in the field of term extraction. The notion of stable lexical marker will be introduced as a method to quantify centrality and dispersion of terms in a specialised domain. As such, the work is a continuation and expansion of so called contrastive approaches to term extraction. The Belgian legal domain will serve as a case study. ispartof: pages:229-248 ispartof: Proceedings TKE 2010: presenting terminology and knowledge engineering resources online: models and challenges (on cd-rom) pages:229-248 ispartof: TKE 2010: Presenting Terminology and Knowledge Engineering Resources Online: Models and Challenges location:Fiontar, Dublin City University, Ireland date:12 Aug - 13 Aug 2010 status: published

ispartof: pages:315-339 ispartof: Cognitive Sociolinguistics: Language Variation in its Structural, Conceptual and Cultural Dimensions pages:315-339 ispartof: LAUD Symposium. Cognitive Sociolinguistics: Language Variation in its Structural, Conceptual and Cultural Dimensions location:Landau/Pfalz (Germany) date:15 Mar - 18 Mar 2010 status: published

Vector-based models of lexical semantics retrieve semantically related words automatically from large corpora by exploiting the property that words with a similar meaning tend to occur in similar contexts. Despite their increasing popularity, it is unclear which kind of semantic similarity they actually capture and for which kind of words. In this paper, we use three vector-based models to retrieve semantically related words for a set of Dutch nouns and we analyse whether three linguistic properties of the nouns influence the results. In particular, we compare results from a dependency-based model with those from a 1st and 2nd order bag-of-words model and we examine the effect of the nouns’ frequency, semantic speficity and semantic class. We find that all three models find more synonyms for high-frequency nouns and those belonging to abstract semantic classses. Semantic specificty does not have a clear influence. ispartof: pages:3243-3249 ispartof: Proceedings of the Sixth International Language Resources and Evaluation (LREC'08) pages:3243-3249 ispartof: Sixth International Language Resources and Evaluation location:Marrakech date:28 May - 30 May 2008 status: published

ispartof: pages:9-16 ispartof: Proceedings of the CoSMO workshop, Roskilde, Denmark pages:9-16 ispartof: International and Interdisciplinary Conference on Modeling and Using Context location:Roskilde date:20 Aug - 24 Aug 2007 status: published

A perennial problem in German syntax is the order of verb arguments in the Mittelfeld. The Mittelfeld is the section of the clause between the two parts of the discontinuous verbal group. In it, all verb arguments can be realized simultaneously, however, not always in the same order. There is a long-standing debate about a number of factors that possibly govern this variation, yet, what their actual influence is, remains unclear. This study takes a quantitative corpus-based approach to the problem and looks specifically at a type of variation that has scarcely been dealt with up to now, viz. the relative order of a pronominal object and a nominal subject in the Mittelfeld. Clauses that show this kind of variation have been collected from the NEGRA-corpus consisting of German newspaper material and they have been annotated for 5 factors frequently mentioned in the literature: grammatical function of the arguments, given/new status and animacy of the arguments' referents, difference in length between the arguments, and their occurrence in either a main or a subordinate clause. The effect of these factors has been statistically checked and modelled in a logistic regression model. The results of the statistical analysis show an effect of all factors except for grammatical. The effect of main versus subordinate clause is especially strong, contradicting earlier hypotheses that this factor is only an epiphenomenon of length difference Departement Linguïstiek. Diensten Faculteit Letteren. Dienst Informatieverwerking Letteren. Centrum voor Grammaticaal en lexicaal betekenisonderzoek. ispartof: pages:320-329 ispartof: Proceedings of the Corpus linguistics 2003 conference - Lancaster: Lancaster university pages:320-329 ispartof: Corpus Linguistics 2003 conference location:Lancaster date:28 Mar - 31 Mar 2003 status: published