Disney Enterprises, Inc.

Joel Branch

James D Williams

Abhik Ray

Tasneem Brutch

Samuel Joseph Reisner

Zvi Topol

Chenna Varri

Methods and systems for measuring and predicting content dissemination in social networks includes computing a 'virality score' for popularity of social media content, a 'pattern' of diffusion of the content, and a &#x201c;hype&#x201d; parameter of such content without requiring a &#x201c;friendship graph&#x201d; or &#x201c;information diffusion&#x201d; structured data. It also includes an iterative, predictive model, which predicts future performance (or future rate of dissemination) of the content while mitigating a class imbalance problem inherent in predicting viral posts, and which provides updates to the model based on actual performance results.

System and method for measuring and predicting content dissemination in social networks

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.

System and method for detection and visualization of anomalous media events

Methods and systems for automatic generation of sports highlights are described, where AV media data of a sporting event (game) are analyzed to identify sports highlights using a data-graph-based technique for 'in-game' highlights, and 'out-of-game' AV media data (e.g. post-game commentary/analysis/news) are analyzed for out-of-game content (OGC) related to each of the selected in-game highlights to produce a collective AV narrative around each of the in-game highlights selected. The format and appearance of the final highlights AV media content or video are also adjustable by the user or the highlights producer to optimize the highlight viewing experience.

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Burbank, CA, United States of America

Joel Branch