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Online reviews significantly impact consumers' decision-making process and firms' economic outcomes and are widely seen as crucial to the success of online markets. Firms, therefore, have a strong incentive to manipulate ratings using fake reviews. This presents a problem that academic researchers have tried to solve for over two decades and on which platforms expend a large amount of resources. Nevertheless, the prevalence of fake reviews is arguably higher than ever. To combat this, we collect a dataset of reviews for thousands of Amazon products and develop a general and highly accurate method for detecting fake reviews. A unique difference between previous datasets and ours is that we directly observe which sellers buy fake reviews. Thus, while prior research has trained models using laboratory-generated reviews or proxies for fake reviews, we are able to train a model using actual fake reviews. We show that products that buy fake reviews are highly clustered in the product reviewer network. Therefore, features constructed from this network are highly predictive of which products buy fake reviews. We show that our network-based approach is also successful at detecting fake review buyers even without ground truth data, as unsupervised clustering methods can accurately identify fake review buyers by identifying clusters of products that are closely connected in the network. While text or metadata can be manipulated to evade detection, network-based features are more costly to manipulate because these features result directly from the inherent limitations of buying reviews from online review marketplaces, making our detection approach more robust to manipulation. Conflict of interest statement

在上一篇文章中（相关阅读：战“疫”期间，首饰消毒要当心！《人民日报》发布8种消毒剂使用指南（上） ），J先生给大家讲了含氯消毒剂（84消毒液）、含碘类消毒剂、酚类消毒剂、季铵盐类消毒剂、含溴消毒剂、二氧化氯消毒液等不适合给首饰消毒的消毒剂。

那么，有哪些消毒剂相对适合给首饰进行消毒呢？今天，J先生继续来给大家说一说~

相对适合给首饰消毒的消毒剂

醇类消毒剂，就是我们日常生活中常见的酒精类消毒剂，在这次疫情中，官方公布最有效的消毒方法之一就是75%的酒精。