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There is an extensive literature on fake-review detection on online platforms such as Amazon, Yelp, and Tripadvisor. This literature has proposed methods for detection based on text features, image features, spatiotemporal differences, network features, sentiment, and others (see the many references in ref. 4). One of the main hurdles in creating algorithms capable of detecting fake reviews is the lack of ground truth data, that is, reviews that are known to be fake, and this literature has been criticized for relying on low-quality proxies (4). Significance

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There is an extensive literature on fake-review detection on online platforms such as Amazon, Yelp, and Tripadvisor. This literature has proposed methods for detection based on text features, image features, spatiotemporal differences, network features, sentiment, and others (see the many references in ref. 4). One of the main hurdles in creating algorithms capable of detecting fake reviews is the lack of ground truth data, that is, reviews that are known to be fake, and this literature has been criticized for relying on low-quality proxies (4). Significance

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Global Approach

Global Approach

Global Approach