Python学习笔记之 中英文文本情感分析

代码

#英文情感分析 textblob
from textblob import TextBlob
import nltk
text = 'I am so happy. I am so sad.'
blob = TextBlob(text)
print(blob)
print(blob.sentences)
print(blob.sentences[0].sentiment)
print(blob.sentences[1].sentiment)
print(blob.sentiment)

#中文情感分析SnowNLP
from snownlp import SnowNLP
text = u'我很高兴啊。 我很难过。'
s = SnowNLP(text)
for sentence in s.sentences:
    print(sentence)
s1 = SnowNLP(s.sentences[0])
s2 = SnowNLP(s.sentences[1])
print(s1.sentiments)
print(s2.sentiments)

输出结果

I am so happy. I am so sad.
[Sentence(“I am so happy.”), Sentence(“I am so sad.”)]
Sentiment(polarity=0.8, subjectivity=1.0)
Sentiment(polarity=-0.5, subjectivity=1.0)
Sentiment(polarity=0.15000000000000002, subjectivity=1.0)
我很高兴啊
我很难过
0.6732684101105153
0.847689058310992

吐槽

英文情感分析textblob识别文本正面或者负面，一般区间是-1~1
中文情感分析snownlp的结果很诧异，自带语料库中的准确率可见一斑，“我很难过”这句话有84%的概率是正面情感，OH~~~

标签：中英文,Python,am,SnowNLP,so,blob,sentences,print,文本
来源： https://blog.csdn.net/weixin_42392800/article/details/121443959