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User sentiment analysis based on social network information and its application in consumer reconstruction intention

机译:基于社交网络信息的用户情感分析及其在消费者重构意图中的应用

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Due to the increasingly fierce competition in the consumer goods market, customer retention strategies are of great importance for enterprises to maintain their dominance and long-term and stable earnings. Understanding customer repurchase intention and re-patronage is the prerequisite and foundation for business and retailers. Online reviews include ratings and emotional information from many customers on brands and online stores. Consumer repurchase intention can be measured by mining the attitudes and emotions of consumers in the reviews. Based on online reviews, this work used textual sentiment calculation and fuzzy mathematics to study the online repurchase intention of online consumers. Taking satisfaction, trust and promotion efforts as the antecedents, and consumer repurchase intention as the consequent, a model was established based on emotional computing and fuzzy reasoning. Through the satisfaction, trust and promotion effort of five sportswear brands in Taobao, we verified the reasoning for determining consumer repurchase intention of products. Meanwhile, the relationship between the initial purchase intention and repurchase intention of consumers was compared, thus providing the basis for online stores to formulate their marketing strategy and brand segmentation.
机译:由于消费品市场竞争日趋激烈,客户保留策略对于企业保持优势地位以及长期稳定的收益至关重要。了解客户的回购意图和重新赞助是企业和零售商的前提和基础。在线评论包括来自品牌和在线商店的许多客户的评分和情感信息。可以通过在评论中挖掘消费者的态度和情感来衡量消费者的回购意向。基于在线评论,本文使用文本情感计算和模糊数学研究了在线消费者的在线回购意向。建立了基于情感计算和模糊推理的模型,以满意,信任和促进努力为前提,并以此为依据建立了消费者回购意向。通过淘宝网五个运动服装品牌的满意度,信任度和促销力度,我们验证了确定产品消费者回购意向的理由。同时,比较了消费者的初始购买意愿和回购意愿之间的关系,为网上商店制定营销策略和品牌细分提供了依据。

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