微博情感分析python代码
时间: 2023-10-27 16:05:33 浏览: 61
微博情感分析的Python代码可以使用以下步骤进行实现:
1. 导入所需的库和模块:
```python
import requests
import re
import json
import jieba
import matplotlib.pyplot as plt
from wordcloud import WordCloud
from snownlp import SnowNLP
```
2. 获取微博数据:
```python
def get_weibo_data(url):
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
response = requests.get(url, headers=headers)
if response.status_code == 200:
return response.text
return None
```
3. 解析微博评论:
```python
def parse_comments(html):
pattern = re.compile(r'"text": "(.*?)",', re.S)
comments = re.findall(pattern, html)
return comments
```
4. 进行情感分析:
```python
def sentiment_analysis(comments):
sentiments = []
for comment in comments:
s = SnowNLP(comment)
sentiments.append(s.sentiments)
return sentiments
```
5. 可视化展示情感分析结果:
```python
def visualize_sentiments(sentiments):
plt.hist(sentiments, bins=20, color='green', alpha=0.8)
plt.xlabel('Sentiment Score')
plt.ylabel('Number of Comments')
plt.title('Sentiment Analysis of Weibo Comments')
plt.show()
```
6. 统计常用表情并进行词云展示:
```python
def generate_wordcloud(comments):
words = ' '.join(comments)
wordcloud = WordCloud(font_path='simhei.ttf', background_color='white').generate(words)
plt.imshow(wordcloud, interpolation='bilinear')
plt.axis('off')
plt.show()
```
7. 调用函数执行微博情感分析:
```python
url = 'https://api.weibo.com/2/comments/show.json?id=123456789'
html = get_weibo_data(url)
comments = parse_comments(html)
sentiments = sentiment_analysis(comments)
visualize_sentiments(sentiments)
generate_wordcloud(comments)
```