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基于电商用户评论数据,自动识别情感倾向并提取关键产品优缺点,生成结构化分析报告以辅助运营决策。
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Please analyze the provided e-commerce platform user review data, identifying the sentiment polarity (positive, negative, or neutral) of each review, and extracting specific product features or issues mentioned. For negative reviews, further summarize the main reasons for complaints; for positive reviews, summarize the core factors for user satisfaction. Finally, output a structured sentiment analysis report containing sentiment distribution statistics, high-frequency keyword clouds, and specific suggestions for product improvement. Ensure the analysis results are objective, accurate, and actionable, helping the operations team optimize product descriptions and service processes.
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请分析提供的电商平台用户评论数据,识别每条评论的情感倾向(正面、负面或中性),并提取评论中提及的具体产品特性或问题点。对于负面评论,需进一步归纳主要投诉原因;对于正面评论,需总结用户满意的核心因素。最终输出一份结构化的情感分析报告,包含情感分布统计、高频关键词云及针对产品改进的具体建议,确保分析结果客观、准确且具备可执行性,帮助运营团队优化产品描述和服务流程。
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