Tracking Virality in Social Graphs via Downstream Action Attribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing user-action metrics fail to accurately track the impact of an individual's actions on a website, leading to underestimated user interest, incorrect assessments of audience, and reduced value of paid advertising due to the lack of tracking of subsequent 'downstream' actions by other users.
Innovation Solution
A method to aggregate and analyze information on multiple users' actions within a social graph, including direct and indirect components, to determine the comprehensive impact of a user's action, using a geometric series model to estimate the indirect effects and improve metrics such as revenue and profitability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing user-action metrics are used to track user interest, then the tracking system is simple, but the measurement precision is low because downstream actions by other users are not captured
Solution Approach 1:
The patent segments user actions into direct actions (performed by the user themselves) and downstream actions (performed by other users influenced by the initial user). This segmentation allows the system to track and measure different types of actions separately, improving measurement precision by capturing the full impact chain while maintaining manageable system complexity through structured data collection.
Solution Approach 2:
The patent introduces an intermediary attribution system that connects initial user actions to downstream actions through social graph relationships. This intermediary mechanism tracks the influence chain between users, enabling precise measurement of downstream effects without requiring direct monitoring of all user interactions across the platform.
2Loss of information
If downstream actions are not tracked, then the tracking system remains simple, but the loss of information occurs because the full impact of user actions is underestimated
Solution Approach 1:
The patent implements a feedback mechanism where downstream actions are tracked and attributed back to the initial user actions that caused them. This feedback loop provides complete information about the full impact of user actions, eliminating information loss and enabling better decision-making by showing the true extent of user influence through social networks.
3Reliability
If traditional user-action metrics are used, then the assessment process is simple, but the reliability is low because audience size and advertising value are incorrectly assessed
Solution Approach 1:
The patent creates a universal tracking framework that can assess multiple metrics simultaneously (audience size, engagement impact, advertising value) by tracking the same underlying downstream actions. This multi-functional approach improves reliability across different assessment dimensions while avoiding the need for separate complex systems for each metric.
Data Source
AI summary
A technique for determining the impact of multiple users' actions is described. According to this technique, information specifying multiple users' actions is aggregated. This information includes linkages that indicate the initiators of the multiple users' actions. Then, the impacts of the multiple users' actions are determined based on the aggregated information. In particular, the impact of a given user's action includes a direct component performed by the given user and an indirect component performed by other users in a social graph in response to the given user's action, where the social graph includes relationships between the other users and the given user. For example, the multiple users' actions and the social graph may be associated with a website, and the determined impacts may allow traffic and/or revenue of the website to be increased.