Sentiment analysis for sentences in spanish
Project description
sentiment-spanish
How does it work?
sentiment-spanish is a python library that uses convolutional neural networks to predict the sentiment of spanish sentences. The model was trained using over 800000 reviews of users of the pages eltenedor, decathlon, tripadvisor, filmaffinity and ebay. This reviews were extracted using web scraping with the project opinion-reviews-scraper
Using the rate in the user reviews we trained the model to learn from the language in them. For that we use the libraries Keras and Tensorflow. We achieved a validation accuracy (accuracy over fresh data, no used for training) of 88%. For more details regarding the training of the neural network model check the repo sentiment-analysis-model-neural-network
Why?
I believe there are not many solutions to sentiment analysis in spanish based on neural networks.
Install and use
First to install the package
pip install sentiment-analysis-spanish
You will also need keras and tensorflow
pip install keras tensorflow
Import the package
from sentiment_analysis_spanish import sentiment_analysis
run the sentiment analysis:
sentiment = sentiment_analysis.SentimentAnalysisSpanish()
print(sentiment.sentiment("me gusta la tombola es genial"))
you will see that it outputs
1
For instance if you use the text
sentiment = sentiment_analysis.SentimentAnalysisSpanish()
print(sentiment.sentiment("me parece terrible esto que me estás diciendo"))
you will see that it outputs
9.460418e-14s
which as you see is very close to 0.
Output and meaning
The function sentiment(text) returns a number between 0 and 1. This is the probability of string variable text of being "positive". Low probabilities mean that the text is negative (numbers close to 0), high probabilities (numbers close to 1) mean that the text is positive. The space in between corespond to neutral texts.
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