Python+Django+爬虫+情感分析+机器/深度学习==搭建舆情分析系统——上篇（某博热搜数据用户主题与评论数据为例：代码非常仔细，值得借鉴，由于篇幅过长，分为上中下篇）

# 导入必要的模块
import requests
from bs4 import BeautifulSoup
import jieba
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from wordcloud import WordCloud
import re
 
# 设置一些基本的常量
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'}
stopwords = pd.read_csv('stopwords.txt', index_col=False, sep='\t', quoting=3)
stopwords = stopwords['word'].values.tolist()
 
# 爬取某博文章的热搜标题
def get_baidu_hot_search(date):
    url = 'http://top.baidu.com/buzz?b=1&p=1&d=1'
    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.text, 'lxml')
    titles = soup.find_all('a', {'class': 'list-title'})
    times = soup.find_all('span', {'class': 'list-num'})
    result = []
    for title, time in zip(titles, times):
        result.append({
            'title': title.get_text(),
            'search_num': time.get_text()
        })
    return result
 
# 获取文本情感倾向
def get_sentiment(text):
    # 这里应该是情感分析的代码，例如调用某个情感分析API或者模型
    # 返回情感分值，例如正面分值和负面分值
    pass
 
# 分析某一天的热搜情感
def analyze_sentiment_on_day(date):
    hot_searches = get_baidu_hot_search(date)
    titles = [hs['title'] for hs in hot_searches]
    results = []
    for title in titles:
        # 这里应该是调用情感分析函数，并将结果添加到results列表中
        pass
    return results
 
# 绘制热搜词云
def draw_word_cloud(text):
    wordlist = jieba.cut(text)
    wordspace_split = ' '.join(wordlist)
    stopwords_list = stopwords
    wordcloud = WordCloud(background_color="white",
                          mask=plt.imread('china_location_map.png'),
                          stopwords=stopwords_list,
                          font_path='simhei.ttf',
                          max_words=200,
                          max_font_size=100,
                          random_state=42)
    mywordcloud = wordcloud.generate(wordspace_split)
    plt.imshow(mywordcloud)
    plt.axis('off')
    plt.show()
 
# 主函数
if __name__ == '__main__':
    date = '2020-01-01'
    results = analyze_sentiment_on_day(date)
    text = ' '.join([result['title'] for result in results])
    draw_word_cloud(text)

这个代码实例提供了一个框架，展示了如何使用Python爬取某博热搜数据，并使用结巴分词、去停用词、绘制词云等方法来分析这些数据。这个过程是构建舆情分析系统的一个基本步骤，它教会用户如何进行基本的文本处理和情感