Social Media Feed Composition via Congruent Object Matching
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Solution Overview
Problem
Current recommendation systems on social media platforms are intrusive and lack personal touch, often displaying repetitive ads that users find off-putting, and fail to provide relevant content that resonates with users' interests beyond product-focused approaches.
Innovation Solution
The system compares congruent objects in media assets posted on social media platforms with recommendations from an advertisement server, scoring and ranking them for relevance, and determining their display order to create a personalized experience by priming users with soft to hard reinforcement strategies, using media assets from user contacts or third parties that share congruent objects with secondary content items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional recommendation systems display ads based on user browsing history and product focus, then ad relevance to user interests is improved, but user intrusiveness and negative user experience increase
Solution Approach 1:
The patent introduces user contacts (friends, family, colleagues) as intermediaries between the advertising system and the target user. Instead of directly showing product-focused ads to users, the system displays media assets from their contacts that naturally contain or relate to the advertised products. This intermediary approach makes recommendations feel more personal and less intrusive, as they appear to come from social connections rather than corporate advertising systems.
Solution Approach 2:
The system performs preliminary actions by having user contacts post or share media assets containing the advertised products before the target user sees them. This creates a natural warming-up effect where users are exposed to product-related content in a organic, social context before encountering direct advertisements, reducing the shock and intrusiveness of subsequent ad exposure.
2Productivity
If recommendation systems use direct product advertising, then advertising effectiveness is improved, but personal touch and user engagement decrease
Solution Approach 1:
User contacts serve as mediators who naturally incorporate advertised products into their media assets. This maintains advertising effectiveness by ensuring product visibility while adding personal touch through the social relationship between contacts and target users. The advertising message is delivered through a personal channel rather than a corporate one.
Solution Approach 2:
The system applies different qualities to different parts of the recommendation system: media assets from contacts have high personal quality and social authenticity, while ads from manufacturers have high production quality and clear messaging. By combining these different qualities in a coordinated way, the system achieves both personal touch and advertising effectiveness.
3Ease of operation
If social media platforms display more personalized content based on user preferences, then user engagement is improved, but system complexity and computational requirements increase
Solution Approach 1:
The system uses universal social graph data and existing media asset databases that already contain user-generated content. Instead of building entirely new recommendation algorithms, the system leverages existing social platform infrastructure (friends, followers, shared content) to deliver personalized recommendations, reducing the need for complex new computational systems.
Solution Approach 2:
User contacts automatically provide the personalized content through their own media posts and shares. The system doesn't need to generate or create content; it simply retrieves and displays content that users have already created and shared. This self-service approach reduces system complexity while maintaining personalization.
Data Source
AI summary
Systems and methods for determining shared congruent objects between warming up media assets and a secondary content item are described. The warming up media assets, along with their reactions, are posted on a social media platform. A secondary content item is identified for display and congruent objects displayed in the secondary content item are used as recommendations to identify the warming up media assets. In some embodiments, the warming media assets do not include a display of the product or service that is the focus of the secondary content item. The congruent objects used as recommendations are determined based on selection of a reinforcement strategy which ranges from a soft to a hard reinforcement. Once a warming up media asset is identified, instructions are transmitted for its display, which may include displaying it at the top of a social media feed and auto-playing the warming up media asset.