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import pandas as pd
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from collections import Counter
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# 读取TXT文件并统计AI相关关键词
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def count_ai_keywords(file_path, output_excel):
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# 定义与AI技术相关的关键词列表
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ai_keywords = [
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"AI", "人工智能", "Machine learning", "机器学习", "Deep learning", "深度学习",
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"Neural network", "神经网络", "自然语言处理", "Natural language processing",
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"计算机视觉", "Computer vision", "Robotics", "机器人", "自动化", "Automation",
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"人脸识别", "Face recognition", "大数据", "数据挖掘", "智能系统", "自动驾驶", "无人驾驶"
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]
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# 用来存储统计结果的Counter
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keyword_count = Counter()
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keyword_danmakus = {keyword: [] for keyword in ai_keywords} # 存储含有每个关键词的弹幕
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# 读取文件
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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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# 遍历每个关键词，统计弹幕中包含关键词的数量，并记录弹幕
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for keyword in ai_keywords:
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if keyword.lower() in line.lower(): # 统计关键词忽略大小写
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keyword_count[keyword] += 1
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keyword_danmakus[keyword].append(line.strip()) # 将弹幕加入对应关键词列表
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# 获取排名前8的关键词
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top_keywords = [keyword for keyword, _ in keyword_count.most_common(8)]
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print("AI 技术相关的前8条弹幕关键词统计：")
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for keyword, count in keyword_count.most_common(8):
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print(f"{keyword}: {count} 条弹幕")
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# 创建一个DataFrame，将前8名关键词的弹幕按列存储
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df_dict = {}
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for keyword in top_keywords:
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df_dict[keyword] = keyword_danmakus[keyword]
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# 将弹幕写入Excel，每个关键词作为一列
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df = pd.DataFrame(dict([(k, pd.Series(v)) for k, v in df_dict.items()]))
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df.to_excel(output_excel, index=False)
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print(f"弹幕已保存至 {output_excel}")
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# 文件路径
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file_path = "danmakus_2024_olympics.txt"
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output_excel = "top_ai_danmakus.xlsx"
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# 调用函数并统计并保存至Excel
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count_ai_keywords(file_path, output_excel)
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