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Der Beitrag stellt die Ergebnisse einer Onlinebenutzungsstudie zur Funktion und Rezeption von Belegen im einsprachigen deutschen Onlinewörterbuch elexiko vor. Diese werden vor dem Hintergrund allgemeiner metalexikographischer und konzeptioneller Überlegungen interpretiert, ein Ausblick führt zu weiteren relevanten Fragestellungen.
We investigate the optional omission of the infinitival marker in a Swedish future tense construction. During the last two decades the frequency of omission has been rapidly increasing, and this process has received considerable attention in the literature. We test whether the knowledge which has been accumulated can yield accurate predictions of language variation and change. We extracted all occurrences of the construction from a very large collection of corpora. The dataset was automatically annotated with language-internal predictors which have previously been shown or hypothesized to affect the variation. We trained several models in order to make two kinds of predictions: whether the marker will be omitted in a specific utterance and how large the proportion of omissions will be for a given time period. For most of the approaches we tried, we were not able to achieve a better-than-baseline performance. The only exception was predicting the proportion of omissions using autoregressive integrated moving average models for one-step-ahead forecast, and in this case time was the only predictor that mattered. Our data suggest that most of the language-internal predictors do have some effect on the variation, but the effect is not strong enough to yield reliable predictions.
Languages employ different strategies to transmit structural and grammatical information. While, for example, grammatical dependency relationships in sentences are mainly conveyed by the ordering of the words for languages like Mandarin Chinese, or Vietnamese, the word ordering is much less restricted for languages such as Inupiatun or Quechua, as these languages (also) use the internal structure of words (e.g. inflectional morphology) to mark grammatical relationships in a sentence. Based on a quantitative analysis of more than 1,500 unique translations of different books of the Bible in almost 1,200 different languages that are spoken as a native language by approximately 6 billion people (more than 80% of the world population), we present large-scale evidence for a statistical trade-off between the amount of information conveyed by the ordering of words and the amount of information conveyed by internal word structure: languages that rely more strongly on word order information tend to rely less on word structure information and vice versa. Or put differently, if less information is carried within the word, more information has to be spread among words in order to communicate successfully. In addition, we find that–despite differences in the way information is expressed–there is also evidence for a trade-off between different books of the biblical canon that recurs with little variation across languages: the more informative the word order of the book, the less informative its word structure and vice versa. We argue that this might suggest that, on the one hand, languages encode information in very different (but efficient) ways. On the other hand, content-related and stylistic features are statistically encoded in very similar ways.
Studying Lexical Dynamics and Language Change via Generalized Entropies: The Problem of Sample Size
(2020)
Recently, it was demonstrated that generalized entropies of order α offer novel and important opportunities to quantify the similarity of symbol sequences where α is a free parameter. Varying this parameter makes it possible to magnify differences between different texts at specific scales of the corresponding word frequency spectrum. For the analysis of the statistical properties of natural languages, this is especially interesting, because textual data are characterized by Zipf’s law, i.e., there are very few word types that occur very often (e.g., function words expressing grammatical relationships) and many word types with a very low frequency (e.g., content words carrying most of the meaning of a sentence). Here, this approach is systematically and empirically studied by analyzing the lexical dynamics of the German weekly news magazine Der Spiegel (consisting of approximately 365,000 articles and 237,000,000 words that were published between 1947 and 2017). We show that, analogous to most other measures in quantitative linguistics, similarity measures based on generalized entropies depend heavily on the sample size (i.e., text length). We argue that this makes it difficult to quantify lexical dynamics and language change and show that standard sampling approaches do not solve this problem. We discuss the consequences of the results for the statistical analysis of languages.
Studying Lexical Dynamics and Language Change via Generalized Entropies: The Problem of Sample Size
(2019)
Recently, it was demonstrated that generalized entropies of order α offer novel and important opportunities to quantify the similarity of symbol sequences where α is a free parameter. Varying this parameter makes it possible to magnify differences between different texts at specific scales of the corresponding word frequency spectrum. For the analysis of the statistical properties of natural languages, this is especially interesting, because textual data are characterized by Zipf’s law, i.e., there are very few word types that occur very often (e.g., function words expressing grammatical relationships) and many word types with a very low frequency (e.g., content words carrying most of the meaning of a sentence). Here, this approach is systematically and empirically studied by analyzing the lexical dynamics of the German weekly news magazine Der Spiegel (consisting of approximately 365,000 articles and 237,000,000 words that were published between 1947 and 2017). We show that, analogous to most other measures in quantitative linguistics, similarity measures based on generalized entropies depend heavily on the sample size (i.e., text length). We argue that this makes it difficult to quantify lexical dynamics and language change and show that standard sampling approaches do not solve this problem. We discuss the consequences of the results for the statistical analysis of languages.
In a recent paper published in the Journal of Language Evolution, Kauhanen, Einhaus & Walkden (KEW) challenge the results presented in one of my papers (Koplenig, Royal Society Open Science, 6, 181274 (2019)), in which I tried to show through a series of statistical analyses that large numbers of L2 (second language) speakers do not seem to affect the (grammatical or statistical) complexity of a language. To this end, I focus on the way in which the Ethnologue assesses language status: a language is characterised as vehicular if, in addition to being used by L1 (first language) speakers, it should also have a significant number of L2 users. KEW criticise both the use of vehicularity as a (binary) indicator of whether a language has a significant number of L2 users and the idea of imputing a zero proportion of L2 speakers to non-vehicular languages whenever a direct estimate of that proportion is unavailable. While I recognise the importance of post-publication commentary on published research, I show in this rejoinder that both points of criticism are explicitly mentioned and analysed in my paper. In addition, I also comment on other points raised by KEW and demonstrate that both alternative analyses offered by KEW do not stand up to closer scrutiny.
This article presents empirical findings about what criteria make for a good online dictionary, using data on expectations and demands collected in an online questionnaire (N~684), complemented by additional results from a second questionnaire (N-390) which looked more closely at whether respondents had differentiated views on individual aspects of the criteria rated in the first study. Our results show that the classical criteria of reference books (such as reliability and clarity) were rated highest by our participants, whereas the unique characteristics of online dictionaries (such as multimedia and adaptability) were rated and ranked as (partly) unimportant. To verify whether or not the poor ratings of these innovative features were a result of the fact that our subjects are unfamiliar with online dictionaries incorporating such features, we incorporated an experiment into the second study. Our results revealed a learning effect: participants in the learning-effect condition, i.e. respondents who were first presented with examples of possible innovative features of online dictionaries, judged adaptability and multimedia to be more useful than participants who were not given that information. Thus, our data point to the conclusion that developing innovative features is worthwhile but that it should be borne in mind that users can only be persuaded of their benefits gradually. In addition, we present data about questions relating to the design of online dictionaries.
Questions of design
(2014)
All lexicographers working on online dictionary projects that do not wish to use an established form of design for their online dictionary, or simply have new kinds of lexicographic data to present, face the problem of what kind of arrangement is best suited for the intended users of the dictionary. In this chapter, we present data about questions relating to the design of online dictionaries. This will provide projects that use these or similar ways of presenting their lexicographic data with valuable information about how potential dictionary users assess and evaluate them. In addition, the answers to corresponding open-ended questions show, detached from concrete design models, which criteria potential users value in a good online representation. Clarity and an uncluttered look seem to dominate in many answers, as well as the possibility of customization, if the latter is not connected with a too complex usability model.
Quantitativ ausgerichtete empirische Linguistik hat in der Regel das Ziel, grose Mengen sprachlichen Materials auf einmal in den Blick zu nehmen und durch geeignete Analysemethoden sowohl neue Phanomene zu entdecken als auch bekannte Phanomene systematischer zu erforschen. Das Ziel unseres Beitrags ist es, anhand zweier exemplarischer Forschungsfragen methodisch zu reflektieren, wo der quantitativ-empirische Ansatz fur die Analyse lexikalischer Daten wirklich so funktioniert wie erhofft und wo vielleicht sogar systembedingte Grenzen liegen. Wir greifen zu diesem Zweck zwei sehr unterschiedliche Forschungsfragen heraus: zum einen die zeitnahe Analyse von produktiven Wortschatzwandelprozessen und zum anderen die Ausgleichsbeziehung von Wortstellungsvs. Wortstrukturregularitat in den Sprachen der Welt. Diese beiden Forschungsfragen liegen auf sehr unterschiedlichen Abstraktionsebenen. Wir hoffen aber, dass wir mit ihnen in groser Bandbreite zeigen konnen, auf welchen Ebenen die quantitative Analyse lexikalischer Daten stattfinden kann. Daruber hinaus mochten wir anhand dieser sehr unterschiedlichen Analysen die Moglichkeiten und Grenzen des quantitativen Ansatzes reflektieren und damit die Interpretationskraft der Verfahren verdeutlichen.