Notification Scoring System for Social Network Engagement
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Solution Overview
Problem
Social networking systems face challenges in determining whether to send notifications to users, as existing methods lack effectiveness in predicting user interaction and may lead to unnecessary notifications, which can result in user disengagement.
Innovation Solution
A method is developed to score notifications based on factors such as user demographics, previous social network activity, and content relevance, with a threshold-based decision to send notifications, considering the likelihood of user interaction and the risk of unsubscribing, to optimize notification delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If notifications are sent to users, then user engagement is improved, but user disengagement increases due to unnecessary notifications
Solution Approach 1:
The system changes parameters by scoring notifications based on multiple factors including user demographics, previous social network activity, content relevance, and time since last notification. This parameter transformation enables the system to distinguish between useful and unnecessary notifications, resolving the contradiction by sending only scored notifications above threshold levels, thereby improving reliability while reducing harmful disengagement effects
Solution Approach 2:
The system implements feedback by monitoring user interactions with notifications and adjusting future notification scoring accordingly. The prediction model incorporates user response patterns to continuously refine notification effectiveness, creating a closed-loop system that reduces disengagement while maintaining engagement through adaptive notification delivery
2Productivity
If notifications are sent frequently, then user engagement is improved, but notification fatigue increases leading to unsubscribing
Solution Approach 1:
The system transforms notification delivery from a volume-based approach to a score-based approach. By scoring each notification based on predicted user interaction likelihood and factors including time since last notification, the system maintains appropriate notification volume while eliminating fatigue-causing redundant notifications, thus improving productivity without generating harmful fatigue effects
Solution Approach 2:
The system applies partial action by selectively sending only those notifications that score above the threshold, rather than sending all possible notifications. This partial delivery strategy maintains sufficient notification volume to drive engagement while avoiding excessive notifications that cause fatigue and unsubscribing
3Device complexity
If generic notifications are sent, then system complexity is reduced, but relevance to user interests decreases
Solution Approach 1:
The system changes the approach from simple generic notifications to scored notifications that incorporate multiple user-specific parameters including demographics, activity history, and content relevance. This parameter enrichment increases measurement precision of user interest relevance while the automated scoring process keeps system complexity manageable through algorithmic processing rather than manual configuration
Data Source
AI summary
In one embodiment, a method includes accessing for a user one or more electronic notifications that include information about a social network. The social network includes a plurality of nodes connected by a plurality of edges, with at least one node corresponding to the user. The method further includes determining, for each of the electronic notifications, a score that estimates whether a user interaction with the social network will result if the electronic notification is provided to the user. The method further includes determining, based at least in part on the determined scores, an action to take with respect to the electronic notifications.