7 papers
Word-Centered Semantic Graphs for Interpretable Diachronic Sense Tracking
Imene Kolli, Kai-Robin Lange, Jonas Rieger +1
We propose an interpretable, graph-based framework for analyzing semantic shift in diachronic corpora. For each target word and time slice, we induce a word-centered semantic netwo…
Narrative Shift Detection: A Hybrid Approach of Dynamic Topic Models and Large Language Models
Kai-Robin Lange, Tobias Schmidt, Matthias Reccius +3
With rapidly evolving media narratives, it has become increasingly critical to not just extract narratives from a given corpus but rather investigate, how they develop over time. W…
Identifying economic narratives in large text corpora -- An integrated approach using Large Language Models
Tobias Schmidt, Kai-Robin Lange, Matthias Reccius +3
As interest in economic narratives has grown in recent years, so has the number of pipelines dedicated to extracting such narratives from texts. Pipelines often employ a mix of sta…
ttta: Tools for Temporal Text Analysis
Kai-Robin Lange, Niklas Benner, Lars Grönberg +4
Text data is inherently temporal. The meaning of words and phrases changes over time, and the context in which they are used is constantly evolving. This is not just true for socia…
Zeitenwenden: Detecting changes in the German political discourse
Kai-Robin Lange, Jonas Rieger, Niklas Benner +1
From a monarchy to a democracy, to a dictatorship and back to a democracy -- the German political landscape has been constantly changing ever since the first German national state…
SpeakGer: A meta-data enriched speech corpus of German state and federal parliaments
Kai-Robin Lange, Carsten Jentsch
The application of natural language processing on political texts as well as speeches has become increasingly relevant in political sciences due to the ability to analyze large tex…