pip install snownlp
python
from snownlp import SnowNLP
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
corpus = [
]
vectorizer = TfidfVectorizer()
X = vectorizer.fit_transform(corpus)
X_train, X_test, y_train, y_test = train_test_split(X, labels, test_size=0.2)
clf = SVC()
clf.fit(X_train, y_train)
y_pred = clf.predict(X_test)
for text, label in zip(X_test, y_pred):
sentiment = SnowNLP(text).sentiments
if sentiment > 0.5:
else:
