Asynchronous Co-Watching Reaction Filtering
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Solution Overview
Problem
Current content distribution systems only allow for synchronous consumption of content, where users cannot view reactions from previous viewers at a later time, lacking the ability to asynchronously consume content alongside initial users' reactions.
Innovation Solution
A method and system that record and synchronize user reactions during content consumption, allowing subsequent users to view these reactions if they meet a minimum engagement level, with options to configure which reactions and on which devices to display, using machine learning and AI for facial and audio analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the system records all user reactions during content consumption, then the quantity of reaction data is maximized, but the quality of useful information decreases due to inclusion of minimal or unengaging reactions
Solution Approach 1:
The system changes the parameter of reaction filtering by introducing an engagement threshold that dynamically determines which reactions are recorded and shared. Reactions are analyzed based on engagement parameters (duration, intensity, type) and only those exceeding the threshold are included in the asynchronous viewing experience, thereby improving information quality while maintaining relevant quantity.
Solution Approach 2:
The system extracts and separates engaging reactions from the total set of reactions by applying filtering criteria. Minimal or unengaging reactions are taken out of the shared data stream, while only reactions meeting the engagement threshold are extracted for asynchronous delivery, thus improving the quality of information shared with subsequent viewers.
2Adaptability or versatility
If the system provides reactions on multiple devices, then the versatility of viewing options is improved, but the device complexity increases
Solution Approach 1:
The system implements multi-functionality by enabling reactions to be delivered across multiple device types (mobile devices, tablets, computers, televisions) through a unified asynchronous viewing platform. The same reaction data infrastructure serves multiple viewing contexts and device formats, increasing versatility without requiring separate complex systems for each device type.
Solution Approach 2:
The system introduces an intermediary asynchronous viewing platform that mediates between the original synchronous viewing event and the subsequent viewing experience. This intermediary layer handles the complexity of multi-device delivery, abstracting the technical details while providing universal access to reactions across different devices and viewing scenarios.
3Measurement precision
If the system uses machine learning and AI for reaction analysis, then the precision of engagement detection is improved, but the computational resources and processing time increase
Solution Approach 1:
The system applies partial action by using machine learning and AI for reaction analysis only when necessary - specifically when determining whether reactions meet the engagement threshold for asynchronous sharing. The computational resources are deployed selectively to analyze reactions that could potentially be shared, rather than continuously processing all reactions, thus improving detection precision for relevant reactions while managing computational resource consumption.
Data Source
AI summary
The disclosed computer-implemented method may include determining that a subsequent user is consuming content that was consumed previously by an initial user. The computer may access various reactions by the initial user to the content that were recorded and synchronized as the initial user consumed the content. The computer may further determine that at least some of the reactions by the initial user have an engagement level above a predetermined threshold, and then provide the reactions with engagement levels above the predetermined threshold for presentation to the subsequent user synchronously with the content as the content is consumed by the subsequent user. Various other methods, systems, and computer-readable media are also disclosed.