令牌一起使用如何替换令牌？

Question

我想使用 python 对 COVID-19 主题进行情感分析。问题出现了，像“积极测试”这样的条目接收到积极的极性，尽管这个陈述是消极的声明。我目前的代码如下：

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，我想删除标记“test”和“positive”，如果它们一起使用，并用“ill”替换它们。我应该使用循环还是只会用大量文本耗尽我的计算能力？

非常感谢您的帮助！

Answer 1

我已经解决了我的问题如下：

# 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)

它完成了工作。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。

令牌一起使用如何替换令牌？

How to replace tokens if they are used together?

python

nlp

token

nltk

sentiment-analysis