Persona Abstraction Layer for Privacy-Preserving Ad Targeting
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Solution Overview
Problem
Social networks face challenges in retaining and utilizing user persona data across third-party websites, leading to a loss of personalized information and inefficient content targeting.
Innovation Solution
A method and system that detect social network entities in third-party environments, generate user summaries, and serve persona-targeted content using a persona abstraction layer, preventing direct access to private data while utilizing rich social network information for personalized advertising and content customization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user persona data is shared with third-party websites, then content targeting effectiveness is improved, but user privacy and data security are compromised
Solution Approach 1:
The patent introduces a third-party service as an intermediary between the social network and third-party websites. This service aggregates user persona data and makes it available to websites without requiring direct access to private user information. The intermediary layer enables content targeting while maintaining privacy boundaries, resolving the contradiction between targeting effectiveness and privacy protection.
Solution Approach 2:
The patent extracts and aggregates user persona data into a centralized service that can be consumed by third-party websites. By taking out the raw personal information and transforming it into aggregated persona data, the system enables effective targeting without exposing sensitive individual user details, thus addressing both productivity improvement and privacy protection requirements.
2Productivity
If rich user information is made accessible to third parties, then advertising personalization is improved, but data loss and information security are worsened
Solution Approach 1:
The third-party service acts as a mediator that provides advertising personalization capabilities without transferring raw user data to external websites. The service aggregates and processes user information locally, then delivers only necessary persona data to third parties, preventing data loss while enabling personalized advertising.
Solution Approach 2:
The patent creates a copy of user persona data in an aggregated form that can be shared with third parties. This copy contains the necessary information for advertising personalization but lacks the sensitivity of raw user data. By working with this copied and aggregated information, the system achieves personalization without the data loss risks associated with sharing original user information.
3Productivity
If detailed user profiles are shared across platforms, then content relevance is improved, but system complexity and data management burden increase
Solution Approach 1:
The patent extracts the complex task of managing detailed user profiles from individual websites and consolidates it into a centralized third-party service. This service handles the complexity of data aggregation, processing, and management, while websites only need to consume simplified persona data. This extraction reduces the data management burden on each individual system while maintaining content relevance.
Solution Approach 2:
The third-party service provides a universal interface for content relevance across multiple websites and applications. Instead of each website maintaining its own complex user profiling system, the service provides standardized persona data that can be used anywhere, reducing overall system complexity while improving content relevance through centralized management.
Data Source
AI summary
A method of targeted advertisement distribution based on persona data derived from a social network, wherein the social network includes a plurality of content streams, each content stream associated with a user and a user summary. The method includes the steps of receiving an advertisement request from a third party environment with associated content, identifying a content stream that includes a reference to the third party content, identifying a persona based on the user associated with the identified content stream, and serving an advertisement to the third party environment based on the identified persona.