Word sense induction is an important method to identify possible meanings of words. Word co-occurrences can group word contexts into semantically related topics. Besides the pure words, temporal information provide another dimension to further investigate the development of the word meanings over time. Large digital corpora of written language, such as those that are held by the CLARIN-D centers, provide excellent possibilities for such kind of linguistic research on authentic language data. In this paper, we investigate the evolution of meanings of words with topic models over time using large digital text corpora.
['Christian Pölitz', 'Thomas Bartz', 'Katharina Morik', 'Angelika Storrer']
Investigation of Word Senses over Time Using Linguistic Corpora