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multi_language_sentiment
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A pipeline for sentiment analysis for texts with unknown language.
We use the lingua-language-detector to detect the language and run the text samples through an sentiment analysis appropriate pipeline for that language.
Basic usage for analysing a list of sentences:
import multi_language_sentiment
texts = ["This is a positive sentence", "Tämä on ikävä juttu"]
sentiments = multi_language_sentiment.sentiment(texts)
print(sentiments)
This should print
[{'label': 'positive', 'score': 0.89024418592453}, {'label': 'negative', 'score': 0.8899219632148743}]
The module currently supports the following langauges by default: English, Japanese, Arabic, German, Spanish, French, Chinese, Indonesian, Hindi, Italian, Malay, Portuguese, Swedish, and Finnish.
For other languages, you must supply a path for a HuggingFace sentiment analysis pipeline. To supply a pipelien for a new language, use the models parameter:
import multi_language_sentiment
from lingua import Language
texts = ["This is a positive sentence", "Tämä on ikävä juttu"]
models = {Language.FINNISH: "fergusq/finbert-finnsentiment"}
sentiments = multi_language_sentiment.sentiment(texts, models = models)
Note that the pipeline will split each text sample to a maximum length of 512 characters. The sentiments are aggregated by adding up the scores and taking the largest value.
FAQs
Sentiment analysis pipeline for texts in multiple languages.
We found that multi_language_sentiment demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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