The DYLEN project 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. Therefore it also combines methods from these fields like natural language processing, machine learning, network analysis and statistical analysis as well as data visualization.
The technical implementation, which will build on an existing prototype (Grill et al 2017) will mainly be based on Python and appropriate libraries on Neo4j to store the network and on software for big data analysis , e.g. Apache Spark , Hadoop Yarn, HDFS. Gephi or similar tools will be used to visualize the graphs, and R for the statistical analyses .