A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021.
Add a new parameter alias type2score which can be used to set the score dictionary for both corpora at the same time in a WeightedAvgShift. Specifying a single dictionary using only type2score_1 is already possible, but a parameter type2score would be more natural. Just have to check if type2score is None, and if not, set type2score_1 as type2score. Existing code should then handle
From using xpdf, rvest, and quanteda on United Nations Digital Library search results to applying dictionaries to speeches in United Nations meeting records
A small showcase for topic modeling with the tmtoolkit Python package. I use a corpus of articles from the German online news website Spiegel Online (SPON) to create a topic model for before and during the COVID-19 pandemic.
Add a new parameter alias
type2scorewhich can be used to set the score dictionary for both corpora at the same time in aWeightedAvgShift. Specifying a single dictionary using onlytype2score_1is already possible, but a parametertype2scorewould be more natural. Just have to check iftype2scoreisNone, and if not, settype2score_1astype2score. Existing code should then handle