dostoevsky 0.2.1

Sentiment analysis library for russian language

Dostoevsky

Sentiment analysis library for russian language

Install

Please note that Dostoevsky supports only Python 3.6+

$ pip install dostoevsky

Social networks comment model

This model was trained on RuSentiment dataset and achieves up to ~0.70 F1 score

Usage

First of all, you'll need to download pretrained word embeddings and model:

$ dostoevsky download vk-embeddings cnn-social-network-model

Then, we can build our pipeline: text -> tokenizer -> word embeddings -> CNN

from dostoevsky.tokenization import UDBaselineTokenizer, RegexTokenizer
from dostoevsky.embeddings import SocialNetworkEmbeddings
from dostoevsky.models import SocialNetworkModel

tokenizer = UDBaselineTokenizer() or RegexTokenizer()
tokens = tokenizer.split('всё очень плохо')  # [('всё', 'ADJ'), ('очень', 'ADV'), ('плохо', 'ADV')]

embeddings_container = SocialNetworkEmbeddings()

vectors = embeddings_container.get_word_vectors(tokens)
vectors.shape  # (3, 300) - three words/vectors with dim=300

model = SocialNetworkModel(
  tokenizer=tokenizer,
  embeddings_container=embeddings_container,
  lemmatize=False,
)

messages = [
    'наступили на ногу',
    'всё суперски',
]

results = model.predict(messages)

for message, sentiment in zip(messages, results):
    print(message, '->', sentiment)  # наступили на ногу -> negative

License