Episode Pause Recommendations Using Binge Compulsion Scores
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Solution Overview
Problem
Existing media consumption systems fail to provide effective warnings for binge-watching, as they do not account for the likelihood of each episode to cause binge-watching behavior and often warn users when they are not at risk, or fail to warn users when the risk is high.
Innovation Solution
A media guidance application determines a binge compulsion score for each episode based on how many additional episodes an average user watches after viewing a particular episode, and provides prompts to pause playback when the score exceeds a threshold, thereby addressing the likelihood of binge-watching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If generic warnings are provided when users watch too many episodes, then users are notified of excessive viewing, but the warnings are inefficient because they fail to account for the likelihood of each episode to cause binge-watching
Solution Approach 1:
The patent segments the series into individual episodes and assigns a binge compulsion score to each episode based on historical data about how many additional episodes average users watch after viewing that episode. This segmentation allows the system to provide targeted warnings for specific episodes that are more likely to trigger binge-watching, rather than using generic warnings for all episodes.
Solution Approach 2:
The system performs preliminary analysis of binge-watching patterns from historical data before the user actually engages in binge-watching. By pre-calculating binge compulsion scores for each episode based on aggregate user behavior, the system is prepared to provide timely warnings before the user watches an episode that is likely to trigger excessive viewing, rather than reacting after binge-watching has already occurred.
2Measurement precision
If warnings are provided based on general viewing duration, then the system can detect binge-watching behavior, but the warnings are not based on how other users behaved after watching a particular episode
Solution Approach 1:
The system uses feedback from historical binge-watching data to continuously refine its understanding of which episodes are most likely to trigger binge-viewing. By analyzing aggregate user behavior patterns and updating binge compulsion scores based on actual viewing data, the system improves its measurement precision in detecting at-risk situations while retaining valuable episode-specific information about binge likelihood.
Solution Approach 2:
The patent introduces a new dimension of analysis by assigning numerical binge compulsion scores to individual episodes, transforming the detection approach from solely time-based metrics to a multi-dimensional assessment that incorporates episode characteristics. This dimensional change allows the system to distinguish between episodes that are more likely to trigger binge-watching versus those that are less likely, providing more precise and informative warnings.
3Adaptability or versatility
If the system tracks consumption patterns of multiple users to establish binge compulsion scores, then tailored warnings can be provided, but data collection and processing complexity increases
Solution Approach 1:
The system performs self-service by automatically collecting, processing, and analyzing binge-watching data from multiple users without requiring manual input or intervention. The system autonomously tracks consumption patterns, calculates binge compulsion scores, and generates tailored warnings, reducing the need for complex manual data processing while maintaining high adaptability in providing personalized warnings.
Solution Approach 2:
The system manages complexity by transforming complex multi-user consumption pattern data into simplified binge compulsion score parameters for each episode. This parameter transformation reduces the dimensionality of the data processing requirements while preserving the essential information needed for tailored warnings, making the system more manageable despite the sophisticated analysis performed.
Data Source
AI summary
Systems and methods are provided herein for recommending a pause position during a binge-watching session. A series containing multiple sequential episodes is provided to a user device. Then it is determined whether the user is engaged in binge-watching the series. If the user is binge-watching the series, a binge compulsion score is determined for each episode of the plurality of sequential episodes, where the binge compulsion score is based on how many additional sequential episodes an average user has watched after watching that episode. Then, in response to determining that the binge compulsion score of the next episode corresponds to a threshold, a prompt is generated for display, where the prompt includes a recommendation to the user to pause the series before the next episode begins.