如何解决一起使用时如何替换令牌?
我想用python对主题COVID-19进行情感分析。出现的问题是,尽管“肯定测试”等条目是否定声明,但它们接收到肯定极性。我当前的代码如下:
import nltk
from textblob import TextBlob
from nltk.stem import WordNetLemmatizer
# Setting the test string
test_string = "He was tested positive on Covid-19"
tokens = nltk.word_tokenize(test_string)
# Lemmatizer
wordnet_lemmatizer = WordNetLemmatizer()
tokens_lem_list = []
for word in tokens:
lem_tokens = wordnet_lemmatizer.lemmatize(word,pos="v")
tokens_lem_list.append(lem_tokens)
# List to string
tokens_lem_str = ' '.join(tokens_lem_list)
# Print the polarity of the string
print(TextBlob(tokens_lem_str).sentiment.polarity)
具有以下输出:
0.22727272727272727
Process finished with exit code 0
因此,如果要同时使用令牌,请删除“ test”和“ positive”标记,并用单词“ ill”代替它们。我应该使用循环吗?否则这只会占用大量文本的计算能力吗?
非常感谢您的帮助!
解决方法
我已经解决了以下问题:
# Producing a loop which finds "positive" and "negative" tested string entries
matches_positive = ["test","positive"]
matches_negative = ["test","negative"]
replaced_testing_term_sentence = []
for sentence_lem in sentences_list_lem:
# Constrain to replace "positive tested" by "not healthy"
if all(x in sentence_lem for x in matches_positive):
sentence_lem = [word.replace("positive","not healthy") for word in sentence_lem]
sentence_lem.remove("test")
replaced_testing_term_sentence.append(sentence_lem)
# Constrain to replace "negative tested" by "not ill"
elif all(x in sentence_lem for x in matches_negative):
sentence_lem = [word.replace("negative","not ill") for word in sentence_lem]
sentence_lem.remove("test")
replaced_testing_term_sentence.append(sentence_lem)
# Constrain to remain not matching sentences in the data sample
else:
replaced_testing_term_sentence.append(sentence_lem)
完成工作。选定的替换术语是有意选择的。如果有人看到优化的潜力,我将不胜感激。
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