Affinity Server for Media Audience Estimation
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Solution Overview
Problem
Existing technologies fail to effectively correlate social media content with time-based media events and topics to estimate audience affinities, leading to inefficiencies in advertising and content recommendation strategies.
Innovation Solution
An affinity server determines affinity scores by creating populations of social media users interested in specific events or topics, based on their authored content, and calculates these scores through the intersection of relevant user populations, normalized by population size and other factors, to optimize advertising and content recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If social media content items are used to estimate audience affinities for time based media events, then advertising targeting accuracy is improved, but the complexity of correlating social media content with media events increases
Solution Approach 1:
The patent introduces an affinity server as an intermediary component that mediates between social media content and time-based media events. The affinity server creates populations of social media users based on their authored content and calculates affinity scores by determining intersections between these populations, thereby simplifying the complex correlation task into manageable processing steps.
Solution Approach 2:
The system segments the broad task of audience affinity estimation into distinct components: creating user populations based on social media content, calculating intersections between populations, and generating affinity scores. This segmentation allows each component to be processed independently, reducing overall system complexity while maintaining measurement precision.
2Productivity
If populations of social media users are created and intersections calculated to determine affinity scores, then advertising optimization is improved, but the computational resources and time required increase
Solution Approach 1:
The affinity server performs preliminary actions by pre-creating populations of social media users based on their authored content and storing these populations for future use. This allows affinity scores to be calculated more efficiently when needed, as the population data is already organized and ready for intersection calculations, reducing computation time for advertising optimization tasks.
Data Source
AI summary
An affinity server estimates an affinity between two different time based media events (e.g., TV, radio, social media content stream), between a time based media event and a specific topic, or between two different topics, where the affinity score represents an intersection between the populations of social media users who have authored social media content items regarding the two different events and/or topics. The affinity score represents an estimation of the real world affinity between the real world population of people who have an interest in both time based media events, both topics, or in a time based media event and a topic. One possible threshold for including a social media user in a population may be based on a confidence score that indicates the confidence that one or more social media content items authored by the social media user are relevant to the topic or event in question.