Network-based approaches play an increasingly important role in the analysis of data. Especially in the Digital Humanities (DH), network models have gained importance in recent years because more and more data-based and data-driven research is carried out and the amount of data is increasing (e.g. Big Data).
The project, funded by the go!digital NEXT GENERATION, bridges the fields of linguistics, digital humanities and computer science in order to explore the diachronic dynamics of lexical networks on the basis of large-scale authentic language data. The project will reuse language data that is already available at the ACDH-CH, namely the Austrian Media Corpus (AMC) and the Corpus of Austrian Parliamentary Records (ParlAT). The AMC covers the entire Austrian media landscape of the past 20 years and contains 40 million texts (more than 10 billion tokens).
The ParlAT corpus covers the Austrian parliamentary records of the last 20 years with more than 75 million tokens. From the linguistic perspective, the project will explore the diachronic dynamics of lexical networks and discuss networks-based methods for diachronic linguistics. From the point of view of computer science, the project will apply network theory to a big amount of diachronic linguistic data and discuss new methods for the automatic analysis and comparison of these networks. Furthermore, the project will enrich the already available digital toolbox with a freely available tool for network analysis and visualisation and will enhance already existing data with additional annotations. The project, coordinated by the ACDH-CH with Tanja Wissik as PI, is carried out by an interdisciplinary team from the ACDH-CH, the University of Vienna and the Vienna University of Technology.
- Baumann, Andreas, Julia Neidhardt, and Tanja Wissik. 2019. DYLEN: Diachronic Dynamics of Lexical Networks. In: Declerck, Thierry and John P. McCrae (Eds.),Proceedings of the Poster Session of the 2nd Conference on Language, Data and Knowledge (LDK-PS 2019). Leipzig, Germany, May 21, 2019CEUR Workshop Proceedings 2402, p. 24-28.