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This contribution explores the relationship between the English CEFR (Common European Framework of Reference for Languages) vocabulary levels and user interest in English Wiktionary entries. User interest was operationalized through the number of views of these entries in Wikimedia server logs covering a period of four years (2019–2022). Our findings reveal a significant relationship between CEFR levels and user interest: entries classified at lower CEFR levels tend to attract more views, which suggests a greater user interest in more basic vocabulary. A multiple regression model controlling for other known or potential factors affecting interest: corpus frequency, polysemy, word prevalence, and age of acquisition confirmed that lower CEFR levels attract significantly more views even after taking into account the other predictors. These findings highlight the importance of CEFR levels in predicting which words users are likely to look up, with implications for lexicography and the development of language learning materials.
Less than one percent of words would be affected by gender-inclusive language in German press texts
(2024)
Research on gender and language is tightly knitted to social debates on gender equality and non-discriminatory language use. Psycholinguistic scholars have made significant contributions in this field. However, corpus-based studies that investigate these matters within the context of language use are still rare. In our study, we address the question of how much textual material would actually have to be changed if non-gender-inclusive texts were rewritten to be gender-inclusive. This quantitative measure is an important empirical insight, as a recurring argument against the use of gender-inclusive German is that it supposedly makes written texts too long and complicated. It is also argued that gender-inclusive language has negative effects on language learners. However, such effects are only likely if gender-inclusive texts are very different from those that are not gender-inclusive. In our corpus-linguistic study, we manually annotated German press texts to identify the parts that would have to be changed. Our results show that, on average, less than 1% of all tokens would be affected by gender-inclusive language. This small proportion calls into question whether gender-inclusive German presents a substantial barrier to understanding and learning the language, particularly when we take into account the potential complexities of interpreting masculine generics.
We introduce DeReKoGram, a novel frequency dataset containing lemma and part-of-speech (POS) information for 1-, 2-, and 3-grams from the German Reference Corpus. The dataset contains information based on a corpus of 43.2 billion tokens and is divided into 16 parts based on 16 corpus folds. We describe how the dataset was created and structured. By evaluating the distribution over the 16 folds, we show that it is possible to work with a subset of the folds in many use cases (e.g., to save computational resources). In a case study, we investigate the growth of vocabulary (as well as the number of hapax legomena) as an increasing number of folds are included in the analysis. We cross-combine this with the various cleaning stages of the dataset. We also give some guidance in the form of Python, R, and Stata markdown scripts on how to work with the resource.
Computational language models (LMs), most notably exemplified by the widespread success of OpenAI's ChatGPT chatbot, show impressive performance on a wide range of linguistic tasks, thus providing cognitive science and linguistics with a computational working model to empirically study different aspects of human language. Here, we use LMs to test the hypothesis that languages with more speakers tend to be easier to learn. In two experiments, we train several LMs—ranging from very simple n-gram models to state-of-the-art deep neural networks—on written cross-linguistic corpus data covering 1293 different languages and statistically estimate learning difficulty. Using a variety of quantitative methods and machine learning techniques to account for phylogenetic relatedness and geographical proximity of languages, we show that there is robust evidence for a relationship between learning difficulty and speaker population size. However, contrary to expectations derived from previous research, our results suggest that languages with more speakers tend to be harder to learn.
Filtern, Explorieren, Vergleichen: neue Zugriffsstrukturen und instruktive Potenziale von OWIDplus
(2023)
OWIDplus, das Zusatzangebot zur Wörterbuchplattform OWID, vereint verschiedenste lexikalische Datenbanken, Korpustools und visuell aufbereitete Analysen, die mithilfe von Textsuche und Kategorienfiltern so sortiert werden können, dass Benutzer*innen leicht die für sie interessanten Projekte entdecken können. Eine tiefergehende Beschäftigung mit den Einzelprojekten zeigt, wie bei aller oberflächlicher Ähnlichkeit oder gemeinsamen Themenbereichen ganz unterschiedliche methodische Zugänge zu sprachlichen Daten gewählt worden sind und wie Methodik und Forschungsfrage stets aufeinander abgestimmt werden müssen. Die Vielzahl potenzieller Forschungsfragen führt so unweigerlich zu einer Diversität von Projekten und somit einer Heterogenität, die, so hoffen die Autor*innen, in OWIDplus greifbar wird.
One of the fundamental questions about human language is whether all languages are equally complex. Here, we approach this question from an information-theoretic perspective. We present a large scale quantitative cross-linguistic analysis of written language by training a language model on more than 6500 different documents as represented in 41 multilingual text collections consisting of ~ 3.5 billion words or ~ 9.0 billion characters and covering 2069 different languages that are spoken as a native language by more than 90% of the world population. We statistically infer the entropy of each language model as an index of what we call average prediction complexity. We compare complexity rankings across corpora and show that a language that tends to be more complex than another language in one corpus also tends to be more complex in another corpus. In addition, we show that speaker population size predicts entropy. We argue that both results constitute evidence against the equi-complexity hypothesis from an information-theoretic perspective.
Neologisms, i.e., new words or meanings, are finding their way into everyday language use all the time. In the process, already existing elements of a language are recombined or linguistic material from other languages is borrowed. But are borrowed neologisms accepted similarly well by the speech community as neologisms that were formed from “native” material? We investigate this question based on neologisms in German. Building on the corresponding results of a corpus study, we test the hypothesis of whether “native” neologisms are more readily accepted than those borrowed from English. To do so, we use a psycholinguistic experimental paradigm that allows us to estimate the degree of uncertainty of the participants based on the mouse trajectories of their responses. Unexpectedly, our results suggest that the neologisms borrowed from English are accepted more frequently, more quickly, and more easily than the “native” ones. These effects, however, are restricted to people born after 1980, the so-called millenials. We propose potential explanations for this mismatch between corpus results and experimental data and argue, among other things, for a reinterpretation of previous corpus studies.
Ziel dieses Projekts ist es, Sprachdaten so nah wie möglich am Jetzt zu erheben und analysierbar zu machen. Wir möchten, dass möglichst viele Menschen, nicht nur Sprachwissenschaftlerinnen und Sprachwissenschaftler, in die Lage versetzt werden, Sprachdaten zu explorieren und zu nutzen. Hierzu erheben wir ein Korpus, d. h. eine aufbereitete Sammlung von Sprachdaten von RSS-Feeds deutschsprachiger Onlinequellen. Wir zeichnen die Entwicklung der Analysewerkzeuge von einem Prototyp hin zur aktuellen Form der Anwendung nach, die eine komplette Reimplementierung darstellt. Dabei gehen wir auf die Architektur, einige Analysebeispiele sowie Erweiterungsmöglichkeiten ein. Fragen der Skalierbarkeit und Performanz stehen dabei im Mittelpunkt. Unsere Darstellungen lassen sich daher auf andere Data-Science-Projekte verallgemeinern.
Dieser Beitrag gibt einen Überblick über die methodischen Ausgangspunkte des Projekts MIT. Qualität und stellt einige zentrale Erkenntnisse zur Modellbildung, der korpuslinguistischen Analyse und Akzeptabilitätserhebungen in der Sprachgemeinschaft vor. Wir zeigen dabei, wie bestehende Textqualitätsmodelle anhand einer Analyse einschlägiger Ratgeberliteratur erweitert werden können. Es wurden zwei empirische Fallstudien durchgeführt, die beide auf die Herstellung von textueller Kohärenz mittels des Kausalkonnektors weil fokussieren. Wir stellen zunächst eine korpuskontrastive Analyse vor. Weiterhin zeigen wir, wie man anhand verschiedener Aufgabenstellungen diverse Aspekte von Akzeptabilität in der Sprachgemeinschaft abprüfen kann.
Olaf Scholz gendert. Eine Analyse von Personenbezeichnungen in Weihnachts- und Neujahrsansprachen
(2022)
Schlagzeilen wie die in unserer Überschrift blieben im Januar 2022 aus. Dabei enthielt die erste Neujahrsansprache von Olaf Scholz kein einziges generisches Maskulinum, sondern Doppelformen (Mitbürgerinnen und Mitbürger, Expertinnen und Experten), geschlechtsabstrahierende Ausdrücke (Eltern, Familien, Geimpfte, Menschen) und Personalisierungen bzw. Umschreibungen wie uns allen, es haben sich 60 Millionen […] impfen lassen, oder ich möchte allen danken. Die Rede nutzt somit durchgängig verschiedene Formen geschlechtergerechter Sprache, wohl aber so unauffällige Formen, dass dies keine mediale Aufmerksamkeit auf sich gezogen hat. Nebenbei: Dies zeigt, dass es bei den hitzigen öffentlichen Diskussionen rund um das Thema nicht um alle Formen geschlechtergerechter Sprache geht, sondern eigentlich nur um bestimmte Formen, wie z.B. die Verwendung des Gendersterns. Wir stellen hier einige Beobachtungen basierend auf einem annotierten Korpus von Ansprachen vor, die Sie selbst anhand einer Online-App nachvollziehen können.
Based on the privative derivational suffix -los, we test statements found in the literature on word formation using a – at least in this field – novel empirical basis: a list of affective-emotional ratings of base nouns and associated -los derivations. In addition to a frequency analysis based on the German Reference Corpus, we show that, in general, emotional polarity (so-called valence, positive vs. negative emotions) is reversed by suffixation with -los. This change is stronger for more polarized base nouns. The perceived intensity of emotion (so-called arousal) is generally lower for -los derivations than for base nouns. Finally, to capture the results theoretically, we propose a prototypical -los construction in the framework of Construction Morphology.
Dictionaries have been part and parcel of literate societies for many centuries. They assist in communication, particularly across different languages, to aid in understanding, creating, and translating texts. Communication problems arise whenever a native speaker of one language comes into contact with a speaker of another language. At the same time, English has established itself as a lingua franca of international communication. This marked tendency gives lexicography of English a particular significance, as English dictionaries are used intensively and extensively by huge numbers of people worldwide.
In a recent article, Meylan and Griffiths (Meylan & Griffiths, 2021, henceforth, M&G) focus their attention on the significant methodological challenges that can arise when using large-scale linguistic corpora. To this end, M&G revisit a well-known result of Piantadosi, Tily, and Gibson (2011, henceforth, PT&G) who argue that average information content is a better predictor of word length than word frequency. We applaud M&G who conducted a very important study that should be read by any researcher interested in working with large-scale corpora. The fact that M&G mostly failed to find clear evidence in favor of PT&G's main finding motivated us to test PT&G's idea on a subset of the largest archive of German language texts designed for linguistic research, the German Reference Corpus consisting of ∼43 billion words. We only find very little support for the primary data point reported by PT&G.
Are borrowed neologisms accepted more slowly into the German language than German words resulting from the application of wrd formation rules? This study addresses this question by focusing on two possible indicators for the acceptance of neologisms: a) frequency development of 239 German neologisms from the 1990s (loanwords as well as new words resulting from the application of word formation rules) in the German reference corpus DEREKO and b) frequency development in the use of pragmatic markers (‘flags’, namely quotation marks and phrases such as sogenannt ‘so-called’) with these words. In the second part of the article, a psycholinguistic approach to evaluating the (psychological) status of different neologisms and non-words in an experimentally controlled study and plans to carry out interviews in a field test to collect speakers’ opinions on the acceptance of the analysed neologisms are outlined. Finally, implications for the lexicographic treatment of both types of neologisms are discussed.
In an earlier publication it was claimed that there is no useful relationship between Swahili-English dictionary look-up frequencies and the occurrence frequencies for the same wordforms in Swahili-English corpora, at least not beyond the top few thousand wordforms. This result was challenged using data for German by a different team of researchers using an improved methodology. In the present article the original Swahili-English data is revisited, using ten years’ worth of it rather than just two, and using the improved methodology. We conclude that there is indeed a positive relationship. In addition, we show that online dictionary look-up behaviour is remarkably similar across languages, even when, as in our case, one is dealing with languages from very dissimilar language families. Furthermore, online dictionaries turn out to have minimum look-up success rates, below which they simply cannot go. These minima are language-sensitive and vary depending on the regularity of the searched-for entries, but are otherwise constant no matter the size of randomly sampled dictionaries. Corpus-informed sampling always improves on any random method. Lastly, from the point of view of the graphical user interface, we argue that the average user of an online bilingual dictionary is better served with a single search box, rather than separate search boxes for each dictionary side.
Diachrone Wortschatzveränderungen werden in der Regel exemplarisch anhand bestimmter Phänomene oder Phänomenbereiche untersucht. Wir widmen uns der Frage, ob und wie Wandelprozesse auch auf globaler Ebene, also ohne sich auf bestimmte Wortschatzausschnitte festzulegen, messbar sind. Zur Untersuchung dieser Frage nutzen wir das Spiegel-Korpus, in dem alle Ausgaben der Wochenzeitschrift seit 1947 enthalten sind. Dabei gehen wir auf grundlegende Herausforderungen ein, die es dabei zu lösen gilt, wie die Verteilung sprachlicher Daten und die Folgen unterschiedlicher Subkorpusgrößen, d.h. im konkreten Fall die variierende Größe des Spiegelkorpus über die Zeit hinweg. Wir stellen ein Verfahren vor, mit dem wir in der Lage sind, flankiert von einem „Lackmustest“ zur Überprüfung der Ergebnisse, Wortschatzwandelprozesse bis auf die Mikroebene, d.h. zwischen zwei Monaten oder gar Wochen, quantitativ nachzuvollziehen.
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.
In der Geschichte der Sprachwissenschaft hat das Lexikon in unterschiedlichem Maße Aufmerksamkeit erfahren. In jüngerer Zeit ist es vor allem durch die Verfügbarkeit sprachlicher Massendaten und die Entwicklung von Methoden zu ihrer Analyse wieder stärker ins Zentrum des Interesses gerückt. Dies hat aber nicht nur unseren Blick für lexikalische Phänomene geschärft, sondern hat gegenwärtig auch einen profunden Einfluss auf die Entstehung neuer Sprachtheorien, beginnend bei Fragen nach der Natur lexikalischen Wissens bis hin zur Auflösung der Lexikon-Grammatik-Dichotomie. Das Institut für Deutsche Sprache hat diese Entwicklungen zum Anlass genommen, sein aktuelles Jahrbuch in Anknüpfung an die Jahrestagung 2017 – „Wortschätze: Dynamik, Muster, Komplexität“ – der Theorie des Lexikons und den Methoden seiner Erforschung zu widmen.
Standardisierte statistische Auswertungen von Korpusdaten im Projekt "Korpusgrammatik" (KoGra-R)
(2017)
Wir zeigen anhand dreier Beispielanalysen, wie das im IDS-Projekt „Korpusgrammatik“ entwickelte Auswertungstool KoGra-R in der quantitativlinguistischen Forschung zur Analyse von Frequenzdaten auf mehreren linguistischen Ebenen eingesetzt werden kann. Wir demonstrieren dies anhand regionaler Präferenzen bei der Selektion von Genitivallomorphen, der Variation von Relativpronomina sowie der Verwendung bestimmter anaphorischer Ausdrucke in Abhängigkeit davon, ob sich das Antezedens im gleichen Satz befindet oder nicht. Die in KoGra-R implementierten statistischen Tests sind für jede dieser Ebenen geeignet, um mindestens einen ersten statistisch abgesicherten Eindruck der Datenlage zu erlangen.
Reading corpora are text collections that are enriched with processing data. From a corpus linguist’s perspective, they can be seen as an extension of classical linguistic corpora with human language processing behavior. From a psycholinguist’s perspective, reading corpora allow to test psycholinguistic hypotheses on subsets of language and language processing as it is ‘in the wild’ – in contrast to strictly controlled language material in isolated sentences, as used in most psycholinguistic experiments. In this paper, we will investigate a relevance-based account of language processing which states that linguistic structures, that are embedded deeper syntactically, are read faster because readers allocate less attention to these structures.
We start by trying to answer a question that has already been asked by de Schryver et al. (2006): Do dictionary users (frequently) look up words that are frequent in a corpus. Contrary to their results, our results that are based on the analysis of log files from two different online dictionaries indicate that users indeed look up frequent words frequently. When combining frequency information from the Mannheim German Reference Corpus and information about the number of visits in the Digital Dictionary of the German Language as well as the German language edition of Wiktionary, a clear connection between corpus and look-up frequencies can be observed. In a follow-up study, we show that another important factor for the look-up frequency of a word is its temporal social relevance. To make this effect visible, we propose a de-trending method where we control both frequency effects and overall look-up trends.