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随着社会媒体的兴起,公众舆论对电网企业的运营与决策产生了重要影响。本文旨在通过文本挖掘技术,分析社交媒体上关于电网的舆情信息,以揭示公众对电力相关事件的情感倾向和意见趋势。本文选择新浪微博平台作为舆情数据的主要来源,利用python等工具进行数据收集和数据预处理。通过数据清洗、关键词抽取和情感分析构建文本分析的框架,本实验对微博评论数据进行深入挖掘和解读分析。通过采用情感词典的方法对电力事件相关的微博数据进行分类和情感打分,从而有效地识别出舆情中的正面和负面评论。研究结果揭示了电力事件舆论的核心主题和情感分布,可以帮助电网管理者更好地明确公众的需求与担忧,从而优化电网服务和提升应急响应能力。

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随着社会媒体的兴起,公众舆论对电网企业的运营与决策产生了重要影响。本文旨在通过文本挖掘技术,分析社交媒体上关于电网的舆情信息,以揭示公众对电力相关事件的情感倾向和意见趋势。本文选择新浪微博平台作为舆情数据的主要来源,利用python等工具进行数据收集和数据预处理。通过数据清洗、关键词抽取和情感分析构建文本分析的框架,本实验对微博评论数据进行深入挖掘和解读分析。通过采用情感词典的方法对电力事件相关的微博数据进行分类和情感打分,从而有效地识别出舆情中的正面和负面评论。研究结果揭示了电力事件舆论的核心主题和情感分布,可以帮助电网管理者更好地明确公众的需求与担忧,从而优化电网服务和提升应急响应能力。

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