v0.11.0

New in version 0.11.0: Vectorizers Module

You can now use a set of custom vectorizers for topic modeling over phrases, as well as lemmata and stems.

from turftopic import KeyNMF
from turftopic.vectorizers.spacy import NounPhraseCountVectorizer

model = KeyNMF(
    n_components=10,
    vectorizer=NounPhraseCountVectorizer("en_core_web_sm"),
)
model.fit(corpus)
model.print_topics()

Topic ID	Highest Ranking
	...
3	fanaticism, theism, fanatism, all fanatism, theists, strong theism, strong atheism, fanatics, precisely some theists, all theism
4	religion foundation darwin fish bumper stickers, darwin fish, atheism, 3d plastic fish, fish symbol, atheist books, atheist organizations, negative atheism, positive atheism, atheism index
	...

Turftopic now also comes with a Chinese vectorizer for easier use, as well as a generalist multilingual vectorizer.

from turftopic.vectorizers.chinese import default_chinese_vectorizer
from turftopic.vectorizers.spacy import TokenCountVectorizer

chinese_vectorizer = default_chinese_vectorizer()
arabic_vectorizer = TokenCountVectorizer("ar", remove_stopwords=True)
danish_vectorizer = TokenCountVectorizer("da", remove_stopwords=True)
...