Social Network Content Notification Timing and Filtering
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Solution Overview
Problem
Users in social networking systems face difficulty in identifying relevant content items from multiple groups, leading to decreased interaction and engagement, as they receive a large number of content items, making it hard to determine which are interesting or relevant.
Innovation Solution
The social networking system analyzes user interaction data to determine the most frequent interaction times and scores content items based on user interactions such as preferences, shares, and comments, then presents a curated set of high-scoring items during the user's most active times, adjusting notification frequency based on user engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If users are included in multiple groups to increase content availability, then the quantity of content items increases, but the user's ability to identify relevant content decreases
Solution Approach 1:
The patent segments the large set of content items from multiple groups by applying filtering criteria (user preferences, interaction history, recency) to divide and organize content into manageable, relevant subsets. This segmentation allows users to efficiently identify relevant content without being overwhelmed by the total quantity.
Solution Approach 2:
The system changes parameters such as recency thresholds, interaction frequency weights, and preference match scores to dynamically adjust content relevance. By modifying these parameters based on user behavior, the system optimizes the presentation of content items to improve identifiability while maintaining quantity.
2Quantity of substance
If users receive notifications for all content items from groups, then content delivery completeness increases, but user engagement decreases due to notification overload
Solution Approach 1:
Instead of notifying users about all content items (excessive action), the system applies partial action by selectively notifying only about content items that meet relevance thresholds based on user preferences and interaction patterns. This partial notification approach maintains engagement by avoiding overload while ensuring important content is communicated.
Solution Approach 2:
The system uses feedback from user interactions (clicks, ignores, explicit preferences) to continuously adjust notification thresholds and content selection criteria. This feedback loop optimizes the balance between notification quantity and user engagement, ensuring notifications remain relevant and actionable.
3Loss of information
If the system presents all content items to users, then content completeness is improved, but the time required for users to find relevant content increases
Solution Approach 1:
The system performs preliminary actions by pre-filtering, ranking, and organizing content items based on user preferences, interaction history, and relevance criteria before presentation. This preliminary processing reduces the time users need to search for relevant content while maintaining completeness through systematic coverage of important items.
Solution Approach 2:
The system dynamically changes parameters such as content ranking weights, filtering thresholds, and presentation formats based on user behavior patterns. These parameter adjustments optimize the balance between presenting comprehensive content and minimizing user search time, adapting to individual user needs.
Data Source
AI summary
A social networking system maintains various groups that each include one or more users and maintains information describing interactions by users with the social networking system. Based on interactions with the social networking system by the user, the social networking system determines a time interval when the user most frequently interacts with the social networking system. Additionally, the social networking system selects various content items provided to groups including the user based on amounts of interaction with content items provided to groups including the user by other social networking system users. During the time interval when the user most frequently interacts with the social networking system, information identifying a set of the selected content items is presented to the user via the social networking system.


