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import requests
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import re
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import pandas as pd
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import time
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from collections import Counter
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import jieba
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import wordcloud
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import imageio
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# 全局变量定义
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video_num = 300 # 定义要爬取的视频数量
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stopwords_path = r'C:\Users\ly130\Desktop\Homework1\停用词.txt' # 定义停用词文件的路径
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ai_keyword_list = ['AI', '智能'] # 定义与AI相关的关键词列表
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# 设置请求头和基础URL
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headers = {
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"User-Agent": 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
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"cookie": "buvid4=B85AEC97-F69C-C637-E3C2-C663D774232B87096-022081317-Mk4wjKcJQ45KiYrEq7vrds65fs3pUAqkDfUodWgIWmefZ%2B8Gkn9QRg%3D%3D; CURRENT_FNVAL=4048; buvid_fp=ae1a9ed67ce4b4b81601b1428b3217f9; rpdid=|(k|lk~umYk)0J'u~um~Y|lku; SESSDATA=19c9c747%2C1735394649%2Cde0b5%2A72CjCGWwVQmSRSWbmZZg7l2IVicrrImP6KbqADlDdybFU35A2pNwxPiQvGuSWVPFCvg4sSVjNCOVZTU3ZjeXhGcTYwc1RZSWo1U2E2clc2WkJwdE0zREh2SnRnaldDcGhDUTZOVnF2TVdIWVZvVXBuNnJGeWs5MlhvNFdraGZpaGFwbVNvSXlWSERRIIEC; bili_jct=b7b181986a9d1a649b30eb2fa5929d52; DedeUserID=1604567014; DedeUserID__ckMd5=e19ded6239c7cd47; buvid3=3D25DBF7-1426-D2BB-E102-DB9D3B6CE68458040infoc; b_nut=1719933858; enable_web_push=DISABLE; header_theme_version=CLOSE; LIVE_BUVID=AUTO8417216581143780; fingerprint=4a6a977133f772625df973e6fe4b955c; bp_video_offset_1604567014=968870267503771648; hit-dyn-v2=1; CURRENT_QUALITY=80; _uuid=DEA107613-17109-A8AA-9E27-E8BA6FBFC103E89699infoc; bili_ticket=eyJhbGciOiJIUzI1NiIsImtpZCI6InMwMyIsInR5cCI6IkpXVCJ9.eyJleHAiOjE3MjU3OTUyODcsImlhdCI6MTcyNTUzNjAyNywicGx0IjotMX0.4xQbg9vPDx7yeSRK4xst2CzX32eMjPSMdlfFyeUn6_g; bili_ticket_expires=1725795227; PVID=8; bp_t_offset_1604567014=974079272559837184; b_lsid=351B10593_191C81CD95D; home_feed_column=4; browser_resolution=978-740; sid=6zbnnd1f"
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}
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base_url = "https://search.bilibili.com/video?keyword=2024%E5%B7%B4%E9%BB%8E%E5%A5%A5%E8%BF%90%E4%BC%9A&from_source=webtop_search&spm_id_from=333.1007&search_source=3"
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def get_bv(max_videos):
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"""从Bilibili搜索结果中获取视频的BV号。
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Args:
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max_videos (int): 最大视频数量。
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Returns:
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list: 视频的BV号列表。
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"""
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bv_set = set()
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for index in range(1, 11):
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if len(bv_set) >= max_videos:
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break
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searchpage_url = base_url + f"&page={index}&page_size=30"
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try:
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response = requests.get(searchpage_url, headers=headers)
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response.raise_for_status()
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data = response.text
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bv_set.update(re.findall('href="//www.bilibili.com/video/(.*?)/"', data))
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except requests.RequestException as e:
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print(f"请求错误: {e}")
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bv_list = list(bv_set)[:max_videos]
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print("爬取bv号完成，共", len(bv_list), "个bv号")
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return bv_list
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def get_oid(bv_list):
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"""根据BV号获取视频的OID号。
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Args:
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bv_list (list): 视频的BV号列表。
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Returns:
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list: 视频的OID号列表。
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"""
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oids = []
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for bv in bv_list:
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video_url = f"https://api.bilibili.com/x/player/pagelist?bvid={bv}&jsonp=jsonp"
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try:
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response = requests.get(video_url, headers=headers)
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response.raise_for_status()
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data = response.text
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oid_match = re.search('"cid":(.*?),"page":', data)
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if oid_match:
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oids.append(oid_match.group(1))
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except requests.RequestException as e:
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print(f"请求错误: {e}")
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return oids
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def get_danmu(oids):
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"""根据OID号获取视频的弹幕内容。
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Args:
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oids (list): 视频的OID号列表。
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Returns:
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list: 弹幕内容列表。
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"""
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content_new = []
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for idx, cid in enumerate(oids, start=1):
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danmu_url = f'https://api.bilibili.com/x/v1/dm/list.so?oid={cid}'
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try:
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response = requests.get(danmu_url, headers=headers)
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response.raise_for_status()
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response.encoding = response.apparent_encoding
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data = response.text
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danmu_list = re.findall(r'<d p=".*?">(.*?)</d>', data)
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content_new.extend(danmu_list)
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print("爬取视频", idx, "弹幕, 获取到：", len(danmu_list), "条弹幕")
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time.sleep(0.5) # 为了安全爬取，设置延时
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except requests.RequestException as e:
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print(f"请求错误: {e}")
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return content_new
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def save_danmu(content_new):
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"""将弹幕内容保存到文本文件和Excel文件中。
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Args:
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danmu_list (list): 弹幕内容列表。
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"""
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processed_text = []
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for word in content_new:
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word = re.findall(r'[^\x00-\x1F\x7F]+', word)
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processed_text.extend(word)
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print(processed_text)
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with open('弹幕.txt', 'w', encoding='utf-8') as f:
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f.write('\n'.join(processed_text))
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df = pd.DataFrame({'弹幕内容': processed_text})
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df.to_excel('所有弹幕.xlsx', index=False)
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print("弹幕保存完成")
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def get_ai_danmu(content):
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"""筛选出与AI相关的弹幕内容并进行排序，将前8个输出到Excel文件中。
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Args:
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content (list): 弹幕内容列表。
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"""
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ai_danmu = [word for word in content if any(keyword in word for keyword in ai_keyword_list)]
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word_count = Counter(ai_danmu).most_common(8)
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df = pd.DataFrame({'词频': [i[1] for i in word_count], '词语': [i[0] for i in word_count]})
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df.to_excel('AI弹幕词频统计.xlsx', index=False)
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print("AI弹幕已保存")
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def load_stopwords(path):
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"""从文件中加载停用词。
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Args:
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path (str): 停用词文件的路径。
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Returns:
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set: 停用词集合。
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"""
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try:
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with open(path, 'r', encoding='utf-8') as f:
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return set(line.strip() for line in f)
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except FileNotFoundError:
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print("停用词文件未找到")
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return set()
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def generate_word_cloud(text, stopwords_path):
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"""根据弹幕内容生成词云。
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Args:
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text (str): 弹幕文本内容。
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stopwords_path (str): 停用词文件的路径。
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"""
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stopwords = load_stopwords(stopwords_path)
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words = jieba.lcut(text)
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c = Counter(word for word in words if len(word) > 1 and word not in stopwords)
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word_list = c.most_common(200)
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image = imageio.v2.imread(r'C:\Users\ly130\Desktop\Homework1\mask.png')
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wc = wordcloud.WordCloud(width=image.shape[0], height=image.shape[1], background_color='white',
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font_path='msyh.ttc', mask=image, scale=3)
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wc.generate_from_frequencies(dict(word_list))
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wc.to_file(r'C:\Users\ly130\Desktop\Homework1\word_cloud123.png')
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if __name__ == '__main__':
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bv_list = get_bv(video_num)
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oid_list = get_oid(bv_list)
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content_new = get_danmu(oid_list)
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save_danmu(content_new)
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get_ai_danmu(content_new)
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with open('弹幕.txt', 'r', encoding='utf-8') as f:
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text = f.read()
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generate_word_cloud(text, stopwords_path)
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