Abstract: Methods and systems for detection and visualization of anomalous media events are described, where AV media data of a sporting event (game) are analyzed to identify AV media segments indicative of unscripted anomalous events (AE's) that elicit a social media response (SMR), and selectable AE graphic visualization (or AE GUI) is provided showing the position of the AE on the court or field of play graphic, corresponding to the actual field of play, as a form of augmented reality. The graphic may also show the level of interest and the sentiment allocation (positive, negative, neutral) for each AE, a social media source allocation, details about the AE, social media posts, and other graphic display features related to the AE. Feedback may also be provided to adjust the logic that identifies AE. AE Alerts may also be sent to users autonomously or based on user-set parameters.

Abstract: Methods and systems for detection and visualization of anomalous media events are described, where AV media data of a sporting event (game) are analyzed to identify AV media segments indicative of unscripted anomalous events (AE's) that elicit a social media response (SMR), and selectable AE graphic visualization (or AE GUI) is provided showing the position of the AE on the court or field of play graphic, corresponding to the actual field of play, as a form of augmented reality. The graphic may also show the level of interest and the sentiment allocation (positive, negative, neutral) for each AE, a social media source allocation, details about the AE, social media posts, and other graphic display features related to the AE. Feedback may also be provided to adjust the logic that identifies AE. AE Alerts may also be sent to users autonomously or based on user-set parameters.