AuthentiCheck: Validating Google Maps Reviews with Metadata Verification

The increase in fraudulent online reviews is pushing the need for robust verification processes of usergenerated content. This framework, therefore, is proposed for user-generated content verification using data from Google Maps for the detection of fake reviews through a novel metadata cross-validation technique. The framework operates in two stages: First, it utilizes a secure API key to revise to retrieve reviews linked to a specific location identifier from the Google Maps API and then views them in an ordered table for easy scrutiny. In the second stage, metadata are extracted from review images using Python's PIL library., from which it captures the time stamps of capture, geographical coordinates, as well as camera configurations. The approach is executed in a modular two-file system that emphasized attribute-by-attribute analysis and, at the end of the day, searches for metadata duplication or discrepancies between metadata and review content as the means to define a thorough, scalable, and reliable solution for identifying fake reviews.