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import requests
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import re
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import warnings
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import json
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import jieba
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import numpy as np
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from wordcloud import WordCloud, ImageColorGenerator
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import matplotlib.pyplot as plt
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from PIL import Image
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import pandas as pd
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from collections import Counter
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#发送请求
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headers = {
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'cookie': 'b_nut=1659613422; buvid3=6C07DC9F-EE29-7F28-2B63-1BF4ECD504A422941infoc; '
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'CURRENT_FNVAL=4048; header_theme_version=CLOSE; '
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'buvid4=92532619-00E5-BF92-443B-595CD15DE59481123-023013113-97xIUW%2FWJtRnoJI8Rbvu4Q%3D%3D;'
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' enable_web_push=DISABLE; rpdid=|(u))kkYu|J|0J\'u~u|)u)RR); '
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'hit-dyn-v2=1; FEED_LIVE_VERSION=V_WATCHLATER_PIP_WINDOW3; '
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'LIVE_BUVID=AUTO2617189721183630; PVID=1; buvid_fp_plain=undefined; '
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'CURRENT_QUALITY=80; _uuid=8108A2C6D-A7AD-7F210-B10E5-EA35A5B47DA391233infoc; '
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'home_feed_column=5; browser_resolution=1545-857; '
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'bsource=search_bing; fingerprint=0c7279b7c69b9542a76b8d9df9b7872a; '
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'buvid_fp=0c7279b7c69b9542a76b8d9df9b7872a; '
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'bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjU0NTE2MTEsImlhdCI6MTcyNTE5MjM1MSwicGx0IjotMX0.9HAkh-aLUFL3i2asyrGNSGwvZnlCdO1qHnr8KCPYRAY; '
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'bili_ticket_expires=1725451551; b_lsid=B7B10E6101_191B8F11FA5; bp_t_offset_1760559884=973015460700225536;'
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' SESSDATA=96c7142d%2C1740938493%2C3a910%2A92CjCc4yaZOS0NpMlzpaXXFlyvjHEGHEZxVtH8JQp1M7im9KrgmNTYIP2F2prPQh4WI4gSVjJtTUt1dGVjMk9SMk9HNkl5MXRWV0tISnNlYzJndGhFVFR1SHVVLWt4UTJjLS1VQ0h1THFmcUY2UU5BV1Jsa2VjTGxDYnpFcnppLVNBQkp3VXdjYzVnIIEC; '
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'bili_jct=3a65db4d1ef7bc981b1673000e0bc73c; DedeUserID=1760559884;'
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' DedeUserID__ckMd5=b5c900381ecb7bcd; sid=ojanxj62',
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'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36 Edg/127.0.0.0'
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}
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cnt = 1
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# 获取弹幕地址
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def GetDanMuUrl(video_str):
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url = video_str
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response = requests.get(url=url, headers=headers)
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html = response.text
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cid = re.search('"cid":(.*?),', html).groups()[0]
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danmu_url = f'https://comment.bilibili.com/{cid}.xml'
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return danmu_url
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# 获取bv号
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def GetBvid(url, pos):
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# 通过搜索api“https://api.bilibili.com/x/web-interface/search/all/v2?page=1-15&keyword=”获取前300个视频的bvid
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res = requests.get(url=url, headers=headers).text
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json_dict = json.loads(res)
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return json_dict["data"]["result"][11]["data"][pos]["bvid"]
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# 获取视频地址
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def GetVedio(bv):
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vedio_url = "https://www.bilibili.com/video/"+bv
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return vedio_url
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# 统计弹幕次数
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def CountDanmu():
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# 打开TXT文件以读取数据
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file_path = '弹幕.txt'
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# 初始化一个空的文本字符串，用于累积所有文本数据
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danmu_list = []
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with open(file_path, 'r', encoding='utf-8') as file:
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for line in file:
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# 在这里处理每一行的数据
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# 示例：将每一行的弹幕添加到danmu_list列表中
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danmu_list.append(line.strip())
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# 使用Counter统计弹幕出现次数
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danmu_counter = Counter(danmu_list)
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# 先筛选与AI技术应用相关的弹幕
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ai_danmu_counter = {k: v for k, v in danmu_counter.items() if 'AI' in k or '人工智能' in k}
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# 然后将筛选后的弹幕转换为Counter对象
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ai_danmu_counter = Counter(ai_danmu_counter)
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# 最后获取AI技术应用方面数量排名前8的弹幕
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top_8_ai_danmus = ai_danmu_counter.most_common(8)
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# 打印排名前8的AI技术应用方面的弹幕及其出现的次数
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for idx, (danmu, count) in enumerate(top_8_ai_danmus, 1):
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print(f'排名 #{idx}: 弹幕 "{danmu}" 出现次数：{count}')
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# 将AI技术应用方面的统计数据写入Excel表格中
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df = pd.DataFrame(list(ai_danmu_counter.items()), columns=['弹幕', '次数'])
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df.to_excel('AI技术应用弹幕统计.xlsx', index=False)
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# 生成词云图
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def make_graph():
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text_data = ''
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with open('AI_danmu.txt', 'r', encoding='utf-8') as file:
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for line in file:
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text_data += line.strip() + ' '
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# 使用jieba进行中文分词
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words = jieba.cut(text_data, cut_all=False)
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word_list = " ".join(words) #列表转成字符串
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# 创建词云图对象，并设置形状
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wordcloud = WordCloud(width=2000,
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background_color='white',
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mask=shape_mask, # 使用自定义形状
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contour_width=1,
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contour_color='white', # 边框颜色
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font_path='STKAITI.TTF', # 用于中文显示的字体文件
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max_words=30000, # 最多显示的词语数量
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colormap='Blues', # 颜色映射，可以根据需要更改
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).generate(word_list)
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# 使用形状图片的颜色
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image_colors = ImageColorGenerator(shape_mask)
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wordcloud.recolor(color_func=image_colors)
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def main():
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# warnings.filterwarnings("ignore")
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global cnt
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for i in range(15):
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url = f'https://api.bilibili.com/x/web-interface/search/all/v2?page={i}&keyword=2024巴黎奥运会'
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for j in range(20):
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print(cnt)
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cnt += 1
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vedio_url_data = vedio_url_data(bv)
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danmu_url = danmu_url(vedio_url_data)
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# print(DanmuUrl)
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response = requests.get(url=danmu_url, headers=headers)
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response.encoding = response.apparent_encoding
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pattern = '<d p=".*?">(.*?)</d>'
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datalist = re.findall(pattern, response.text)
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# print(DataList)
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f = open('弹幕.txt', mode='a', encoding='utf-8')
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for k in range(len(datalist)):
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f.write(datalist[k]+'\n')
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f.close()
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warnings.filterwarnings("ignore")
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CountDanmu()
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make_graph()
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if __name__ == '__main__':
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main()
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