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import pandas as pd
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from collections import Counter
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# 读入所有弹幕
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with open('all_content.txt', mode='r', encoding='utf-8') as f:
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data_list = f.readlines()
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# AI技术应用有关关键词
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keywords = ['AI','人工智能','ai音效','ai视频','ai技术','机器学习', '深度学习', '自然语言处理','ai训练',
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'大模型','自然语言处理','云计算','AI设计','AI图','神经网络', '自动驾驶','ai设计','ai图','AI软件',]
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# 筛选有关AI的弹幕
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selectdanmu = [danmu for danmu in data_list if any(keyword in danmu for keyword in keywords)]
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# 统计弹幕数量
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num = Counter(selectdanmu)
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top_common = num.most_common(8)
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# 展示数量前八条弹幕
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print(top_common)
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t = pd.DataFrame(top_common, columns=['弹幕内容', '数量'])
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# 导出excel文件
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excel_path = 'top8_ai_danmu.xlsx'
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import pandas as pd
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from collections import Counter
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# 读入所有弹幕
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with open('all_content.txt', mode='r', encoding='utf-8') as f:
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data_list = f.readlines()
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# AI技术应用有关关键词
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keywords = ['AI','人工智能','ai音效','ai视频','ai技术','机器学习', '深度学习', '自然语言处理','ai训练',
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'大模型','自然语言处理','云计算','神经网络', '自动驾驶','ai设计','ai图','ai软件',]
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# 筛选有关AI的弹幕
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selectdanmu = [danmu for danmu in data_list if any(keyword in danmu for keyword in keywords)]
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# 统计弹幕数量
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num = Counter(selectdanmu)
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top_common = num.most_common(8)
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# 展示数量前八条弹幕
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print(top_common)
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t = pd.DataFrame(top_common, columns=['弹幕内容', '数量'])
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# 导出excel文件
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excel_path = 'top8_ai_danmu.xlsx'
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t.to_excel(excel_path, index=False)
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