Social Gravity Proximity Content Targeting
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Solution Overview
Problem
Social networking systems face challenges in providing relevant content to users based on their geographic proximity to other users or entities, as existing methods lack the ability to effectively leverage real-world interactions and relationships in their content-targeting models.
Innovation Solution
The system detects proximity events between users and entities, calculates an influence score based on social gravity and duration of proximity, and uses this information to determine if content objects should be sent to users, enhancing location-based services by integrating real-world interactions with online social network relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses traditional content-targeting models without geographic proximity data, then the system complexity remains low, but the content relevance to users deteriorates
Solution Approach 1:
The patent merges traditional content-targeting models with geographic proximity detection by integrating location data from mobile devices with social-networking system data. This combination allows the system to consider both online social relationships and offline physical proximity, thereby improving content relevance without requiring a complete system overhaul
Solution Approach 2:
The patent introduces an intermediary component that processes geographic proximity events and translates them into influence scores that can be integrated into existing content-targeting models. This intermediary layer allows the system to incorporate location-based information without directly complicating the core content delivery mechanism
2Measurement precision
If the system collects and processes geographic proximity data from mobile devices, then the content relevance improves, but the data processing complexity increases
Solution Approach 1:
The patent extracts only the essential geographic proximity information needed for content targeting from mobile device data, rather than processing all available location data. By selectively extracting proximity events and filtering out unnecessary data, the system maintains location accuracy while reducing processing complexity
Solution Approach 2:
The patent implements partial processing of location data by focusing only on significant proximity events that meet certain thresholds, rather than continuously analyzing all location changes. This approach processes sufficient data to maintain relevance without the excessive complexity of comprehensive real-time location tracking
3Productivity
If the system integrates real-world proximity interactions with online social network relationships, then the content engagement improves, but the computational requirements increase
Solution Approach 1:
The patent performs preliminary calculations of influence scores based on proximity events and social graph data in advance, before content delivery is needed. By pre-processing this information and storing it in an optimized format, the system reduces the computational energy required during actual content generation and delivery operations
Data Source
AI summary
A method includes detecting a proximity event associated with a first user and a second user, wherein the proximity event includes the second user being in geographic proximity to the first user and calculating an influence score associated with the proximity event, wherein the influence score is based at least in part on a social gravity of the second user and a duration of the proximity event. The method further includes, upon determining that the influence score is greater than a threshold score, identifying, based at least in part on a geographic location of the first user, a content object associated with the second user for provision to the first user and sending the content object to a client system associated with the first user for display.