Abstract: A computerized-method for detecting market sentiment manipulation that is related to financial-instruments trading. The computerized-method includes: (i) monitoring incoming alerts in an analytics-engine. (ii) retrieving data from each alert, by operating a context-extraction module; (iii) for each alert: a. collecting feeds from social-media servers based on the retrieved data by operating a social-media feeds-extraction module; b. for each feed, generating a summary by using Gen AI; and c. analyzing a social-media sentiment by providing the generated summary of each feed to the Gen-AI; (iv) for each financial instrument that has been traded in the preconfigured period, searching an anomaly between a sentiment from traditional news source and the analyzed social-media sentiment; (v) storing each anomaly in an anomalies database; and (vi) pausing each financial-transaction that has been processed and related to the financial-instrument in the anomalies database.

Abstract: A computerized-method for detecting market sentiment manipulation that is related to financial-instruments trading. The computerized-method includes: (i) monitoring incoming alerts in an analytics-engine. (ii) retrieving data from each alert, by operating a context-extraction module; (iii) for each alert: a. collecting feeds from social-media servers based on the retrieved data by operating a social-media feeds-extraction module; b. for each feed, generating a summary by using Gen AI; and c. analyzing a social-media sentiment by providing the generated summary of each feed to the Gen-AI; (iv) for each financial instrument that has been traded in the preconfigured period, searching an anomaly between a sentiment from traditional news source and the analyzed social-media sentiment; (v) storing each anomaly in an anomalies database; and (vi) pausing each financial-transaction that has been processed and related to the financial-instrument in the anomalies database.