Video Revenue Sharing Through Predictive Popularity Scoring
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Solution Overview
Problem
Existing video hosting systems fail to allow individual users to generate revenue from popular videos and do not predict future popularity, missing opportunities for advertisement placement.
Innovation Solution
A system and method that includes a popularity evaluation module to assess video popularity, a review module to determine eligibility for a revenue sharing program, a user invitation module to invite eligible users, and a payment system to distribute revenue, utilizing a popularity score based on historical data from social networks and micro-blogging sites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If advertisements are placed on videos only when they are already popular, then revenue can be generated from popular videos, but the system misses profitable opportunities to place advertisements on future popular videos before they become popular
Solution Approach 1:
The system performs preliminary actions by predicting which videos will become popular in the future before they actually gain popularity. The popularity prediction module analyzes current video metrics and trends to identify videos that are likely to become popular, allowing the system to proactively place advertisements on these videos in advance, thus capturing revenue opportunities that would otherwise be missed.
2Measurement precision
If the system monitors popularity data from multiple third party sites to predict future popularity, then the system can identify future popular videos, but the complexity of the system increases
Solution Approach 1:
The system implements a universal popularity evaluation mechanism that can assess videos across multiple third-party platforms (social networks, micro-blogging sites, blogs) using a unified prediction model. This multi-functional approach allows the same system architecture to handle diverse data sources and video platforms, improving prediction accuracy without proportionally increasing system complexity through standardized interfaces and centralized processing.
Data Source
AI summary
Media items to be hosted at an asset hosting platform and submitted by an owner of the media items are received. The media items are provided for consumption by users of the asset hosting platform. The historical data identifies a historical popularity of one or more of the media items. Whether the historical data associated with the one or more of the media items satisfies a viewership rate specifying a rate of viewership over a predetermined period of time for the one or more of the media items is determined. Responsive to determining that the historical data associated with the one or more of the media items satisfies the viewership rate, the owner is determined as eligible to participate in a performance sharing program. A communication for a client device associated with the owner of the media items to invite the owner to participate in the performance sharing program is generated.