Notification Aggregation for Social Networking Systems
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Solution Overview
Problem
Conventional networking systems face issues with usability, flexibility, efficiency, security, and accuracy, particularly for users with large followings, including cluttered interfaces, overwhelming notifications, inefficient resource usage, inflexible account types, and inaccurate digital security measures.
Innovation Solution
The system intelligently detects, ranks, and prioritizes engagement notifications, provides flexible account types, and offers secure, accurate growth insights to streamline user engagement and improve user experience by filtering and aggregating notifications, and offering customizable account settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional systems provide all engagement notifications to users, then users receive complete information about co-user interactions, but users become overwhelmed and interfaces become cluttered
Solution Approach 1:
The notification system segments engagement notifications into different categories and priority levels. High-priority notifications (e.g., direct messages, meaningful interactions) are presented individually, while low-priority notifications (e.g., routine likes, comments) are aggregated into summary notifications. This segmentation allows users to receive complete information without being overwhelmed by the volume of individual notifications.
Solution Approach 2:
Multiple low-priority engagement notifications are merged into a single aggregated notification. Instead of presenting hundreds of individual notifications separately, the system combines them into one summary that provides complete information about the engagement while maintaining a clean, usable interface.
2Loss of information
If conventional systems process and store all engagement notifications, then complete engagement data is maintained, but computing resources and storage capacity are wasted
Solution Approach 1:
The system extracts only the essential engagement data that users need to know, separating it from redundant notification data. By taking out only the critical information for processing and storage, the system maintains complete engagement data integrity while significantly reducing computing resource consumption and storage requirements.
Solution Approach 2:
Instead of processing all notifications and then filtering what users see, the system inverts the approach by pre-aggregating and prioritizing notifications before full processing. This inversion allows the system to maintain data completeness while minimizing the computational overhead of processing and storing every individual notification.
3Measurement precision
If conventional systems provide detailed account measurements, then users gain accurate insights about their following, but digital privacy and security concerns arise due to third-party access
Solution Approach 1:
The networking system acts as an intermediary that provides accurate account measurements and engagement analytics directly to users through secure, built-in tools. This eliminates the need for users to share credentials with third-party services, maintaining measurement precision while ensuring digital security and privacy protection.
4Adaptability or versatility
If conventional systems offer multiple account types, then users can find suitable options, but flexibility is reduced when account types are rigid and misrepresentative
Solution Approach 1:
The account type system is made dynamic and flexible, allowing users to easily switch between different account types (personal, creator, business) based on their evolving needs. This dynamic approach ensures that users can accurately represent themselves to co-users while maintaining access to a variety of account options, resolving the rigidity problem of conventional systems.
Data Source
AI summary
The present disclosure relates to systems, non-transitory computer-readable media, and methods for improving and streamlining user engagement with co-users within a networking system. For instance, the user engagement system can detect co-user engagement with a user of a networking system. Based on one or more metrics, such as characteristics of the engaging co-user, the type of detected co-user engagement, or engagement history with the user, the user engagement system can rank, prioritize, and/or aggregate the engagement notifications. For example, the user engagement system can prioritize message requests from co-users with whom the user has not actively engaged on the networking system. In another example, the user engagement system can filter messages from co-users with whom the user has actively engaged in to one of multiple message repositories.


