Measure the similarity between two corpora (text datasets). The measures work best when each corpus is at least 10k words.

from corpus_similarity import Similarity
cs = Similarity(language = "eng")

result = cs.calculate(corpus1, corpus2)

The package contains all preprocessing and training. Only the language needs to be specified. A list of supported languages is provided below.

The Similarity.calculate method requires two input corpora. These can be a list of strings or a filename (supports .txt and .gz files).

The output is a scalar measure of how similar the two corpora are. The values fall between 0 (very different) and 1 (very similar). The values are consistent within languages, but not across languages. For example, Swedish has higher relative similarity than Estonian.

pip install corpus_similarity

pip install git+https://github.com/jonathandunn/corpus_similarity.git

Pacific Languages

haw, Hawaiian (Polynesian)

mri, te reo (Polynesian)

smo, Samoan (Polynesian)

ton, Tongan (Polynesian)

ceb, Cebuano (Austronesian)

mlg, Malagasy (Austronesian)

msa, Malay (Austronesian)

tgl, Tagalog (Austronesian)

Other Languages

vie, Vietnamese

ind, Indonesian

tgl, Tagalog

tam, Tamil

tel, Telugu

bul, Bulgarian

ces, Czech

lav, Latvian

pol, Polish

rus, Russian

slv, Slovenian

ukr, Ukrainian

dan, Danish

deu, German

eng, English

nld, Dutch

nor, Norwegian

swe, Swedish

ell, Greek

fas, Farsi

hin, Hindi

urd, Urdu

cat, Catalan

fra, French

glg, Galician

ita, Italian

por, Portuguese

ron, Romanian

spa, Spanish

jpn, Japanese

kor, Korean

ara, Arabic

heb, Hebrew

zho, Chinese

tha, Thai

tur, Turkish

est, Estonian

fin, Finnish

hun, Hungarian