Open Access

In order to satisfy the information needs of a wide range of researchers across a number of disciplines, large textual datasets require careful design, collection, cleaning, encoding, annotation, storage, retrieval, and curation. This daunting set of tasks has coalesced into a number of key themes and questions that are of interest to the contributing research communities: (a) what sampling techniques can we apply? (b) what quality issues should we be aware of? (c) what infrastructures and frameworks are being developed for the efficient storage, annotation, analysis and retrieval of large datasets? (d) what affordances do visualisation techniques offer for the exploratory analysis approaches of corpora? (e) what legal paths can be followed in dealing with IPR and data protection issues governing both the data sources and the query results? (f) how to guarantee that corpus data remain available and usable in a sustainable way?

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.

Following the successes of the ninth conference in 2022 held in the wonderful Santiago de Compostela, Spain, we are pleased to present the proceedings of the 10th edition of International Conference on CMC and Social Media Corpora for the Humanities (CMC-2023). The focal point of the conference is to investigate the collection, annotation, processing, and analysis of corpora of computer-mediated communication (CMC) and social media. Our goal is to serve as the meeting place for a wide variety of language-oriented investigations into CMC and social media from the fields of linguistics, philology, communication sciences, media studies, and social sciences, as well as corpus and computational linguistics, language technology, textual technology, and machine learning. This year’s event is the largest so far with 45 accepted submissions: 32 papers and 13 poster presentations, each of which were reviewed by members of our ever-growing scientific committee. The contributions were presented in five sessions of two or three streams, and a single poster session. The talks in these proceedings cover a wide range of topics, including the corpora construction, digital identities, digital knowledge-building, digitally-mediated interaction, features of digitally-mediated communication, and multimodality in digital spaces. As part of the conference, we were delighted to include two invited talks: an international keynote speech by Unn Røyneland from the University of Oslo, Norway, on the practices and perceptions of researching dialect writing in social media, and a national keynote speech by Tatjana Scheffler from the Ruhr-University of Bochum on analysing individual linguistic variability in social media and constructing corpora from this data. Additionally, participants could take part in a workshop on processing audio data for corpus linguistic analysis. This volume contains abstracts of the invited talks, short papers of oral presentations, and abstracts of posters presented at the conference.

As a part of the ZuMult-project, we are currently modelling a backend architecture that should provide query access to corpora from the Archive of Spoken German (AGD) at the Leibniz-Institute for the German Language (IDS). We are exploring how to reuse existing search engine frameworks providing full text indices and allowing to query corpora by one of the corpus query languages (QLs) established and actively used in the corpus research community. For this purpose, we tested MTAS - an open source Lucene-based search engine for querying on text with multilevel annotations. We applied MTAS on three oral corpora stored in the TEI-based ISO standard for transcriptions of spoken language (ISO 24624:2016). These corpora differ from the corpus data that MTAS was developed for, because they include interactions with two and more speakers and are enriched, inter alia, with timeline-based annotations. In this contribution, we report our test results and address issues that arise when search frameworks originally developed for querying written corpora are being transferred into the field of spoken language.

Making research data publicly available for evaluation or reuse is a fundamental part of good scientific practice. However, regulations such as copyright law can prevent this practice and thereby hamper scientific progress. In Germany, text-based research disciplines have for a long time been mostly unable to publish corpora made from material outside of the public domain, effectively excluding contemporary works. While there are approaches to obfuscate text material in a way that it is no longer covered by the original copyright, many use cases still require the raw textual context for evaluation or follow-up research. Recent changes in copyright now permit text and data mining on copyrighted works. However, questions regarding reusability and sharing of such corpora at a later time are still not answered to a satisfying degree. We propose a workflow that allows interested third parties to access customized excerpts of protected corpora in accordance with current German copyright law and the soon to be implemented guidelines of the Digital Single Market directive. Our prototype is a very lightweight web interface that builds on commonly used repository software and web standards.