Uncovering Semantic Shifts in Climate Discourse among Dutch Parliamentarians: A Dynamic Bernoulli Embeddings Approach

Traditionally, the detection of semantic change has been studied primarly by historians and linguists. However, the advent of new computational methods has enabled more efficient analysis of word usage in large corpora. Previous studies in this domain have relied mainly on Static Word Embeddings Models, which are faced with the challenge of solving the alignment problem when comparing independently trained embeddings. This paper contributes to the field of Natural Language Processing by employing Dynamic Bernoulli Embeddings (D-EMBs) on a Dutch corpus, effectively avoiding the alignment proble... Mehr ...