python文本情感分析代码

以下是一个简单的Python文本情感分析代码示例，使用了nltk库和情感词典：

import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.stem import WordNetLemmatizer

# 下载所需的nltk数据
nltk.download('stopwords')
nltk.download('punkt')
nltk.download('wordnet')
nltk.download('opinion_lexicon')

# 加载情感词典
positive_words = set(word.strip() for word in open('positive-words.txt'))
negative_words = set(word.strip() for word in open('negative-words.txt'))

# 定义函数进行文本情感分析
def sentiment_analysis(text):
    # 分词
    words = word_tokenize(text.lower())
    # 去除停用词
    stop_words = set(stopwords.words('english'))
    words = [word for word in words if word not in stop_words]
    # 词形还原
    lemmatizer = WordNetLemmatizer()
    words = [lemmatizer.lemmatize(word) for word in words]
    # 计算情感得分
    pos_score = neg_score = 0
    for word in words:
        if word in positive_words:
            pos_score += 1
        elif word in negative_words:
            neg_score += 1
    if pos_score > neg_score:
        return 'positive'
    elif pos_score < neg_score:
        return 'negative'
    else:
        return 'neutral'

# 测试代码
text = "I love this movie, it's so good!"
print(sentiment_analysis(text))  # 输出：positive
text = "This restaurant is terrible, I will never come back again."
print(sentiment_analysis(text))  # 输出：negative
text = "The weather today is neither good nor bad."
print(sentiment_analysis(text))  # 输出：neutral

注意，这只是一个简单的示例代码，实际情感分析可能需要更复杂的算法和数据。