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Für die spezifischen Bedürfnisse der Schreibbeobachtung wurde das Orthografische Kernkorpus (OKK) als virtuelles Korpus in DeReKo entwickelt. Mit derzeit rund 14 Mrd. Token deckt es den Schriftsprachgebrauch in den deutschsprachigen Ländern im Zeitraum von 1995 bis in die Gegenwart ab. Der Zugriff über die Korpusanalyseplattform KorAP erlaubt nicht nur die Nutzung verschiedener Annotationen, sondern über die API-Schnittstellen auch die Einbindung in diverse Auswertungsumgebungen wie RStudio über den RKorAPClient und macht es so für zahlreiche Analyse- und Visualisierungsmöglichkeiten zugänglich.
It is well known that the distribution of lexical and grammatical patterns is size- and register-sensitive (Biber 1986, and later publications). This fact alone presents a challenge to many corpus-oriented linguistic studies focusing on a single language. When it comes to cross-linguistic studies using corpora, the challenge becomes even greater due to the lack of high-quality multilingual corpora (Kupietz et al. 2020; Kupietz/Trawiński 2022), which are comparable with respect to the size and the register. That was the motivation for the creation of the European Reference Corpus EuReCo, an initiative started in 2013 at the Leibniz Institute for the German Language (IDS) together with several European partners (Kupietz et al. 2020). EuReCo is an emerging federated corpus, with large virtual comparable corpora across various languages and with an infrastructure supporting contrastive research. The core of the infrastructure is KorAP (Diewald et al. 2016), a scalable open-source platform supporting the analysis and visualisation of properties of texts annotated by multiple and potentially conflicting information layers, and supporting several corpus query languages. Until recently, EuReCo consisted of three monolingual subparts: the German Reference Corpus DeReKo (Kupietz et al. 2018), the Reference Corpus of Contemporary Romanian Language (Barbu Mititelu/Tufiş/Irimia 2018), and the Hungarian National Corpus (Váradi 2002). The goal of the present submission is twofold. On the one hand, it reports about the new component of EuReCo: a sample of the National Corpus of Polish (Przepiórkowski et al. 2010). On the other hand, it presents the results of a new pilot study using the newly extended EuReCo. This pilot study investigates selected Polish collocations involving light verbs and their prepositional / nominal complements (Fig. 1) and extends the collocation analyses of German, Romanian and Hungarian (Fig. 2) discussed in Kupietz/Trawiński (2022).
The International Comparable Corpus (ICC) (Kirk/Čermáková 2017; Čermáková et al. 2021) is an open initiative which aims to improve the empirical basis for contrastive linguistics by compiling comparable corpora for many languages and making them as freely available as possible as well as providing tools with which they can easily be queried and analysed. In this contribution we present the first release of written language parts of the ICC which includes corpora for Chinese, Czech, English, German, Irish (partly), and Norwegian. Each of the released corpora contains 400k words distributed over 14 different text categories according to the ICC specifications. Our poster covers the design basics of the ICC, its TEI encoding, a demonstration of using the ICC via different query tools, and an outlook on future plans.
Similar to the European Reference Corpus EuReCo (Kupietz et al. 2020), ICC follows the approach of reusing existing linguistic resources wherever possible in order to cover as many languages as possible with realistic effort in as short a time as possible. In contrast to EuReCo, however, comparable corpus pairs are not defined dynamically in the usage phase, but the compositions of the corpora are fixed in the ICC design. The approaches are thus complementary in this respect. The design principles and composition of the ICC are based on those of the International Corpus of English (ICE) (Greenbaum (ed.) 1996), with the deviation that the ICC includes the additional text category blog post and excludes spoken legal texts (see Čermáková et al. 2021 for details). ICC’s fixed-design approach has the advantage that all single-language corpora in the ICC have the same composition with respect to the selected text types and that this guarantees that the selected broad spectrum of potential influencing variables for linguistic variation is always represented. The disadvantage, however, is that this can only be achieved for quite small corpora and that the generalisability of comparative findings based on the ICC corpora will often need to be checked on larger monolingual corpora or translation corpora (Čermáková/Ebeling/Oksefjell Ebeling forthcoming). Arguing that such issues with comparability and representativeness are inevitable, in one way or the other, and need to be dealt with, our poster will discuss and exemplify the text selections in more detail.
Einleitung
(2023)
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.
Der Beitrag betrachtet das Deutsche Referenzkorpus DeReKo in Bezug auf Strategien für seinen Ausbau, den Zugriff über die Korpusanalyseplattform KorAP und seine Einbettung in Forschungsinfrastrukturen und in die deutschsprachige und europäische Korpuslandschaft. Ausgehend von dieser Bestandsaufnahme werden Perspektiven zu seiner Weiterentwicklung aufgezeigt. Zu den Zukunftsvisionen gehören die Verteilung von Korpussressourcen und die Konstruktion multilingualer vergleichbarer Korpora anhand der Bestände der National- und Referenzkorpora, eine Plattform zur Abgabe und Aufbereitung von Sprachspenden als eine Anwendung von Citizen Science sowie eine Komponente zur automatischen Identifikation von übersetzten bzw. maschinenverfassten Texten.
In order to differentiate between figurative and literal usage of verb-noun combinations for the shared task on the disambiguation of German Verbal Idioms issued for KONVENS 2021, we apply and extend an approach originally developed for detecting idioms in a dataset consisting of random ngram samples. The classification is done by implementing a rather shallow, statistics-based pipeline without intensive preprocessing and examinations on the morphosyntactic and semantic level. We describe the overall approach, the differences between the original dataset and the dataset of the KONVENS task, provide experimental classification results, and analyse the individual contributions of our feature sets.
This paper reports on recent developments within the European Reference Corpus EuReCo, an open initiative that aims at providing and using virtual and dynamically definable comparable corpora based on existing national, reference or other large corpora. Given the well-known shortcomings of other types of multilingual corpora such as parallel/translation corpora (shining-through effects, over-normalization, simplification, etc.) or web-based comparable corpora (covering only web material), EuReCo provides a unique linguistic resource offering new perspectives for fine-grained contrastive research on authentic cross-linguistic data, applications in translation studies and foreign language teaching and learning.
Einleitung
(2023)
Das Deutsche Referenzkorpus DeReKo dient als eine empirische Grundlage für die germanistische Linguistik. In diesem Beitrag geben wir einen Überblick über Grundlagen und Neuigkeiten zu DeReKo und seine Verwendungsmöglichkeiten sowie einen Einblick in seine strategische Gesamtkonzeption, die zum Ziel hat, DeReKo trotz begrenzter Ressourcen für einerseits möglichst viele und andererseits auch für innovative und anspruchsvolle Anwendungen nutzbar zu machen. Insbesondere erläutern wir dabei Strategien zur Aufbereitung sehr großer Korpora mit notwendigerweise heuristischen Verfahren und Herausforderungen, die sich auf dem Weg zur linguistischen Erschließung solcher Korpora stellen.
Dieser Beitrag beschreibt die Motivation und Ziele hinter der Initiative Europäisches Referenzkorpus EuReCo. Ausgehend von den Desiderata, die sich aufgrund der Defizite verfügbarer Forschungsdaten wie monolinguale Korpora, Parallelkorpora und Vergleichskorpora für den Sprachvergleich ergeben, werden die bisherigen und die laufenden Arbeiten im Rahmen von EuReCo präsentiert und anhand vergleichender deutsch-rumänischer Kookkurrenzanalysen neue Perspektiven für kontrastive Korpuslinguistik, die die EuReCo-Initiative öffnet, skizziert.
When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state of the art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.
Enabling appropriate access to linguistic research data, both for many researchers and for innovative research applications, is a challenging task. In this chapter, we describe how we address this challenge in the context of the German Reference Corpus DeReKo and the corpus analysis platform KorAP. The core of our approach, which is based on and tightly integrated into the CLARIN infrastructure, is to offer access at different levels. The graduated access levels make it possible to find a low-loss compromise between the possibilities opened up and the costs incurred by users and providers for each individual use case, so that, viewed over many applications, the ratio between effort and results achieved can be effectively optimized. We also report on experiences with the current state of this approach.
When comparing different tools in the field of natural language processing (NLP), the quality of their results usually has first priority. This is also true for tokenization. In the context of large and diverse corpora for linguistic research purposes, however, other criteria also play a role – not least sufficient speed to process the data in an acceptable amount of time. In this paper we evaluate several state-ofthe-art tokenization tools for German – including our own – with regard to theses criteria. We conclude that while not all tools are applicable in this setting, no compromises regarding quality need to be made.
We present the use of count-based and predictive language models for exploring language use in the German Reference Corpus DeReKo. For collocation analysis along the syntagmatic axis we employ traditional association measures based on co-occurrence counts as well as predictive association measures derived from the output weights of skipgram word embeddings. For inspecting the semantic neighbourhood of words along the paradigmatic axis we visualize the high dimensional word embeddings in two dimensions using t-stochastic neighbourhood embeddings. Together, these visualizations provide a complementary, explorative approach to analysing very large corpora in addition to corpus querying. Moreover, we discuss count-based and predictive models w.r.t. scalability and maintainability in very large corpora.
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.
Twitter data is used in a wide variety of research disciplines in Social Sciences and Humanities. Although most Twitter data is publicly available, its re-use and sharing raise many legal questions related to intellectual property and personal data protection. Moreover, the use of Twitter and its content is subject to the Terms of Service, which also regulate re-use and sharing. This extended abstract provides a brief analysis of these issues and introduces the new Academic Research product track, which enables authorized researchers to access Twitter API on a preferential basis.
The automatic recognition of idioms poses a challenging problem for NLP applications. Whereas native speakers can intuitively handle multiword expressions whose compositional meanings are hard to trace back to individual word semantics, there is still ample scope for improvement regarding computational approaches. We assume that idiomatic constructions can be characterized by gradual intensities of semantic non-compositionality, formal fixedness, and unusual usage context, and introduce a number of measures for these characteristics, comprising count-based and predictive collocation measures together with measures of context (un)similarity. We evaluate our approach on a manually labelled gold standard, derived from a corpus of German pop lyrics. To this end, we apply a Random Forest classifier to analyze the individual contribution of features for automatically detecting idioms, and study the trade-off between recall and precision. Finally, we evaluate the classifier on an independent dataset of idioms extracted from a list of Wikipedia idioms, achieving state-of-the art accuracy.
This paper reports on the efforts of twelve national teams in building the International Comparable Corpus (ICC; https://korpus.cz/icc) that will contain highly comparable datasets of spoken, written and electronic registers. The languages currently covered are Czech, Finnish, French, German, Irish, Italian, Norwegian, Polish, Slovak, Swedish and, more recently, Chinese, as well as English, which is considered to be the pivot language. The goal of the project is to provide much-needed data for contrastive corpus-based linguistics. The ICC corpus is committed to the idea of re-using existing multilingual resources as much as possible and the design is modelled, with various adjustments, on the International Corpus of English (ICE). As such, ICC will contain approximately the same balance of forty percent of written language and 60 percent of spoken language distributed across 27 different text types and contexts. A number of issues encountered by the project teams are discussed, ranging from copyright and data sustainability to technical advances in data distribution.
In this paper, we present our experiences and decisions in dealing with challenges in developing, maintaining and operating online research software tools in the field of linguistics. In particular, we highlight reproducibility, dependability, and security as important aspects of quality management – taking into account the special circumstances in which research software
is usually created.
Die Korpusanalyseplattform KorAP ist von Grund auf sprachenunabhängig konzipiert. Dies gilt sowohl in Bezug auf die Lokalisierung der Benutzeroberfläche als auch hinsichtlich unterschiedlicher Anfragesprachen und der Unterstützung fremdsprachiger Korpora und ihren Annotationen. Diese Eigenschaften dienen im Rahmen der EuReCo Initiative aktuell besonders der Bereitstellung weiterer National- und Referenzkorpora neben DeReKo. EuReCo versucht, Kompetenzen beim Aufbau großer Korpora zu bündeln und durch die Verfügbarmachung vergleichbarer Korpora quantitative Sprachvergleichsforschung zu erleichtern. Hierzu bietet KorAP inzwischen, neben dem Zugang durch die Benutzeroberfläche, einen Web API Client an, der statistische Erhebungen, auch korpusübergreifend, vereinfacht.
Der Beitrag beschreibt die Motivation und Ziele des Europäischen Referenzkorpus EuReCo, einer offenen Initiative, die darauf abzielt, dynamisch definierbare virtuelle vergleichbare Korpora auf der Grundlage bestehender nationaler, Referenz- oder anderer großer Korpora bereitzustellen und zu verwenden. Angesichts der bekannten Unzulänglichkeiten anderer Arten mehrsprachiger Korpora wie Parallel- bzw. Übersetzungskorpora oder rein webbasierte vergleichbare Korpora, stellt das EuReCo eine einzigartige linguistische Ressource dar, die neue Perspektiven für germanistische und vergleichende wie angewandte Korpuslinguistik, insbesondere im europäischen Kontext, eröffnet.
Die Korpusanalyseplattform KorAP wird als Nachfolgesystem zu COSMAS II am Leibniz-Institut für Deutsche Sprache (IDS) entwickelt und erlaubt einen umfassenden Zugriff auf einen Teil von DeReKo (Kupietz et al. 2010). Trotz einiger noch fehlender Funktionalitäten ist KorAP bereits produktiv einsetzbar. Im Folgenden wollen wir am Beispiel der Untersuchung von Social-Media-Korpora einige neue Möglichkeiten und Besonderheiten vorstellen.
Making corpora accessible and usable for linguistic research is a huge challenge in view of (too) big data, legal issues and a rapidly evolving methodology. This does not only affect the design of user-friendly graphical interfaces to corpus analysis tools, but also the availability of programming interfaces supporting access to the functionality of these tools from various analysis and development environments. RKorAPClient is a new research tool in the form of an R package that interacts with the Web API of the corpus analysis platform KorAP, which provides access to large annotated corpora, including the German reference corpus DeReKo with 45 billion tokens. In addition to optionally authenticated KorAP API access, RKorAPClient provides further processing and visualization features to simplify common corpus analysis tasks. This paper introduces the basic functionality of RKorAPClient and exemplifies various analysis tasks based on DeReKo, that are bundled within the R package and can serve as a basic framework for advanced analysis and visualization approaches.
We evaluate a graph-based dependency parser on DeReKo, a large corpus of contemporary German. The dependency parser is trained on the German dataset from the SPMRL 2014 Shared Task which contains text from the news domain, whereas DeReKo also covers other domains including fiction, science, and technology. To avoid the need for costly manual annotation of the corpus, we use the parser’s probability estimates for unlabeled and labeled attachment as main evaluation criterion. We show that these probability estimates are highly correlated with the actual attachment scores on a manually annotated test set. On this basis, we compare estimated parsing scores for the individual domains in DeReKo, and show that the scores decrease with increasing distance of a domain to the training corpus.
This paper addresses long-term archival for large corpora. Three aspects specific to language resources are focused, namely (1) the removal of resources for legal reasons, (2) versioning of (unchanged) objects in constantly growing resources, especially where objects can be part of multiple releases but also part of different collections, and (3) the conversion of data to new formats for digital preservation. It is motivated why language resources may have to be changed, and why formats may need to be converted. As a solution, the use of an intermediate proxy object called a signpost is suggested. The approach will be exemplified with respect to the corpora of the Leibniz Institute for the German Language in Mannheim, namely the German Reference Corpus (DeReKo) and the Archive for Spoken German (AGD).
Der Beitrag untersucht vorhandene Lösungen und neue Möglichkeiten des Korpusausbaus aus Social Media- und internetbasierter Kommunikation (IBK) für das Deutsche Referenzkorpus (DEREKO). DEREKO ist eine Sammlung gegenwartssprachlicher Schriftkorpora am IDS, die der sprachwissenschaftlichen Öffentlichkeit über die Korpusschnittstellen COSMAS II und KorAP angeboten wird. Anhand von Definitionen und Beispielen gehen wir zunächst auf die Extensionen und Überlappungen der Konzepte Social Media, Internetbasierte Kommunikation und Computer-mediated Communication ein. Wir betrachten die rechtlichen Voraussetzungen für einen Korpusausbau aus Sozialen Medien, die sich aus dem kürzlich in relevanten Punkten reformierten deutschen Urheberrecht, aus Persönlichkeitsrechten wie der europäischen Datenschutz-Grundverordnung ergeben und stellen Konsequenzen sowie mögliche und tatsächliche Umsetzungen dar. Der Aufbau von Social Media-Korpora in großen Textmengen unterliegt außerdem korpustechnologischen Herausforderungen, die für traditionelle Schriftkorpora als gelöst galten oder gar nicht erst bestanden. Wir berichten, wie Fragen der Datenaufbereitung, des Korpus-Encoding, der Anonymisierung oder der linguistischen Annotation von Social Media Korpora für DEREKO angegangen wurden und welche Herausforderungen noch bestehen. Wir betrachten die Korpuslandschaft verfügbarer deutschsprachiger IBK- und Social Media-Korpora und geben einen Überblick über den Bestand an IBK- und Social Media-Korpora und ihre Charakteristika (Chat-, Wiki Talk- und Forenkorpora) in DEREKO sowie von laufenden Projekten in diesem Bereich. Anhand korpuslinguistischer Mikro- und Makro-Analysen von Wikipedia-Diskussionen im Vergleich mit dem Gesamtbestand von DEREKO zeigen wir charakterisierende sprachliche Eigenschaften von Wikipedia-Diskussionen auf und bewerten ihren Status als Repräsentant von IBK-Korpora.
The DRuKoLA project
(2019)
DRuKoLA, the accompanying project in the making of the Corpus of Romanian Language, is a cooperation between German and Romanian computer scientists, corpus linguists and linguists, aiming at linking reference corpora of European languages under one corpus analysis tool able to manage big data. KorAP, the analysis tool developed at the Leibniz Institute for the German Language (Mannheim), is being tailored for the Romanian language in a first attempt to reunite reference corpora under the EuReCo initiative, detailed in this paper. The paper describes the necessary steps of harmonization within KorAP and the corpus of Romanian language and discusses, as one important goal of this project, criteria and ways to build virtual comparable corpora to be used for contrastive linguistic analyses.
The user interfaces for corpus analysis platforms must provide a high degree of accessibility for ordinary users and at the same time provide the possibility to answer complex research questions. In this paper, we present the design concepts behind the user interface of KorAP, a corpus analysis platform that has evolved into the main gateway to CoRoLa, the Reference Corpus of Contemporary Romanian Language. Based on established principles of user interface design, we show how KorAP addresses the challenge of providing a user-friendly interface for heterogeneous corpus data to a wide range of users with different research questions.
Introduction
(2019)
This paper reports on the latest developments of the European Reference Corpus EuReCo and the German Reference Corpus in relation to three of the most important CMLC topics: interoperability, collaboration on corpus infrastructure building, and legal issues. Concerning interoperability, we present new ways to access DeReKo via KorAP on the API and on the plugin level. In addition we report about advancements in the EuReCo- and ICC-initiatives with the provision of comparable corpora, and about recent problems with license acquisitions and our solution approaches using an indemnification clause and model licenses that include scientific exploitation.
Distributional models of word use constitute an indispensable tool in corpus based lexicological research for discovering paradigmatic relations and syntagmatic patterns (Belica et al. 2010). Recently, word embeddings (Mikolov et al. 2013) have revived the field by allowing to construct and analyze distributional models on very large corpora. This is accomplished by reducing the very high dimensionality of word cooccurrence contexts, the size of the vocabulary, to few dimensions, such as 100-200. However, word use and meaning can vary widely along dimensions such as domain, register, and time, and word embeddings tend to represent only the most prevalent meaning. In this paper we thus construct domain specific word embeddings to allow for systematically analyzing variations in word use. Moreover, we also demonstrate how to reconstruct domain specific co-occurrence contexts from the dense word embeddings.
Neues von KorAP
(2019)
Korpuslinguistik
(2012)
This presentation introduces a new collaborative project: the International Comparable Corpus (ICC) (https://korpus.cz/icc), to be compiled from European national, standard(ised) languages, using the protocols for text categories and their quantities of texts in the International Corpus of English (ICE).
Das Phänomen Sprache ist in Form des beobachtbaren Sprachgebrauchs fast allgegenwärtig, gleichzeitig bleibt das offenkundig Regel- und Systemhafte dieses Phänomens überraschend ungreifbar. Wegen der überwältigenden Komplexität natürlicher Sprachen entsteht bei jedem Versuch, dieses Systemhafte in einer Theorie mit explanatorischem Anspruch zu fassen, eine breite Kluft zwischen der angestrebten theoretischen Beschreibungsebene einerseits und der phänomenologisch zugänglichen Ebene des Sprachgebrauchs andererseits.
Ausgehend von allgemeinen wissenschaftstheoretischen Überlegungen, wie man angesichts dieser Kluft überhaupt zu hinreichend abgesicherten Erkenntnissen für eine explanatorische Theoriebildung kommen kann, betonen die Autoren die Notwendigkeit, sich dem Untersuchungsgegenstand Sprache mit möglichst wenigen Vorannahmen über diesen Gegenstand selbst zu nähern und sich dabei konsequent von der Empirie leiten zu lassen. Sie werben nachdrücklich für eine emergentistische Perspektive auf Sprache, der zufolge alles Regelhafte und Konventionelle in der Sprache ein Epiphänomen des Sprachgebrauchs ist und von den Sprachteilnehmern fortlaufend ausgehandelt wird. Eine treibende Kraft hierbei ist, so wird argumentiert, der Begriff der Ähnlichkeit. Auf dieser Grundlage wird schließlich ein Forschungsprogramm entworfen, das die Wirkung des Faktors Ähnlichkeit auf die Sprache nachzuzeichnen und dadurch schrittweise zu ähnlichen Generalisierungen zu gelangen versucht wie die Sprachgemeinschaft.
Einleitung
(2018)
Das hier vorgeführte Schienenbild ist das in Anlehnung an Wittenburg (2009) als Erweiterungsinstrument gewählte Mittel in dem Versuch, Computertechnologie, linguistische Forschung und Vernetzung am Institut für Deutsche Sprache in deren rasch wachsenden Vielschichtigkeit zu beschreiben. Hier werden u. a. drei Blickwinkel, der des Technologie entwickelnden Wissenschaftlers, des entwickelnden Nutzers und des Nutzers von Informationstechnologie in der linguistischen Forschung vereint und um eine für den Sprachvergleich neue Dimension, die sprachspezifische Parameter von Analyseinstrumenten miteinander harmonisiert, erweitert.
This paper discusses current trends in DeReKo, the German Reference Corpus, concerning legal issues around the recent German copyright reform with positive implications for corpus building and corpus linguistics in general, recent corpus extensions in the genres of popular magazines, journals, historical texts, and web-based football reports. Besides, DeReKo is finally accessible via the new
corpus research platform KorAP, offering registered users several news features in comparison with its predecessor COSMAS II.
Sehr große Korpora – wie das Deutsche Referenzkorpus DeReKo – bieten eine breite Basis für die empirische Forschung. Sie bringen aber auch Herausforderungen mit sich, da sich weder Eigenschaften ihrer Zusammensetzung noch derer von Recherche- und Analyseergebnissen mit einfachen Mitteln erschließen lassen. Dafür bedarf es Verfahren geschickter Sortierung, Gruppierung oder des Clusterings, kurzum: strukturentdeckender Methoden. In Kombination mit Visualisierungstechniken kann so die Wahrnehmung bestimmter Eigenschaften und Zusammenhänge unterstützt und die Aufmerksamkeit auf bestimmte Phänomene, ggf. in Anlehnung an präferenzrelationale Befunde, gelenkt werden. Neben der illustrativen Funktion geht es in diesem Beitrag vor allem um das erkenntnisleitende Potenzial derartiger Verfahren in Kombination. Aus verschiedenen Bereichen werden Beispiele gezeigt, die am IDS oder in Kooperationen zum Einsatz kommen, sowohl zur dokumentarischen und reflexiven Kontrolle von Eigenschaften der Korpuszusammensetzung als auch hinsichtlich korpusanalytischer Methodik, um die qualitative Interpretation von Analysebefunden und die Abduktion von Hypothesen stimulierend zu unterstützen.
Einleitung
(2018)