电子商务矿井中的金丝雀:利用买方对卖方的信息检测和预测不良体验

Dimitriy V. Masterov, U. Mayer, S. Tadelis
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引用次数: 25

摘要

在线市场的声誉和反馈系统往往存在偏见,因此很难确定卖家的质量。我们使用交易后买方对卖方的信息流量来检测eBay上不满意交易的信号。我们假设,在付款后发送的消息是一个可靠的指标,表明买家可能对购买不满意,特别是当消息中包含与负面体验相关的单词时。卖家负面信息流量的比例预示着与该卖家交易的买家是否会停止在eBay上购买,这意味着平台可以利用这些信息作为卖家质量的额外信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Canary in the e-Commerce Coal Mine: Detecting and Predicting Poor Experiences Using Buyer-to-Seller Messages
Reputation and feedback systems in online marketplaces are often biased, making it difficult to ascertain the quality of sellers. We use post-transaction, buyer-to-seller message traffic to detect signals of unsatisfactory transactions on eBay. We posit that a message sent after the item was paid for serves as a reliable indicator that the buyer may be unhappy with that purchase, particularly when the message included words associated with a negative experience. The fraction of a seller's message traffic that was negative predicts whether a buyer who transacts with this seller will stop purchasing on eBay, implying that platforms can use these messages as an additional signal of seller quality.
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