Consumer reviews are an invaluable aid for businesses in obtaining consumers’ feedback to facilitate their marketing campaigns. However, the rapidly increasing number of consumer reviews makes it difficult for businesses to obtain a comprehensive view of consumer opinions about their products, especially about the highlighted product features. This study presents a framework to provide an understanding of how consumers’ feedback changes over time and what concerns consumers most. The framework presented here contributes to consumer review analysis in three ways. First, a novel model is proposed to extract the feature words that are semantically relevant to each highlighted product feature. Second, consumers’ feedback on each highlighted product feature is converted into a sentiment tendency graph, which may reflect how the feedback changes over time. Third, consumers’ feedback is also summarized, which may reveal what consumers appreciate and what concerns them most. The experimental results show that the proposed model can effectively extract the feature words for each highlighted feature of the product. Moreover, both sentiment tendency graphs and summaries could complement each other and provide a more detailed picture for consumers and manufacturers.

消费者评论是企业获得消费者反馈以促进其营销活动的宝贵帮助。但是，消费者评论的数量迅速增加，使企业很难全面了解消费者对其产品，特别是突出显示的产品功能的消费者意见。这项研究提出了一个框架，以了解消费者的反馈随着时间的变化以及消费者最关注的问题。此处介绍的框架通过三种方式有助于消费者评论分析。首先，提出了一种新颖的模型来提取与每个突出显示的产品特征在语义上相关的特征词。其次，将消费者对每个突出显示的产品功能的反馈转换为情感趋势图，这可能反映出反馈随着时间的变化。第三，还总结了消费者的反馈，可以揭示消费者的欣赏和最关注的问题。实验结果表明，该模型可以有效地提取产品每个突出特征的特征词。此外，情绪趋势图和摘要都可以相互补充，并为消费者和制造商提供更详细的信息。