Social Media Audience Estimation for Media Co-relationship Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional audience measurement methods for media exposure, such as panelist-based systems, are costly and impractical for accurately estimating media exposures across numerous distribution channels, especially with the rise of social media, where collecting statistically significant data becomes challenging.
Innovation Solution
The use of social media messages to identify co-relationships between media by analyzing social media messages posted by users, estimating audiences, and classifying media pairings based on overlapping audience members, allowing for the optimization of media exposure data collection and marketing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional panelist-based audience measurement methods are used, then media exposure data can be collected, but the cost increases and the system becomes impractical for accurately estimating media exposures across numerous distribution channels
Solution Approach 1:
The patent uses social media platforms as an intermediary to collect audience measurement data. Instead of directly monitoring traditional panelists across multiple distribution channels, the system leverages social media messages (tweets, posts, etc.) as a proxy to infer media exposure patterns, thereby reducing system complexity while maintaining measurement accuracy
Solution Approach 2:
The patent creates a copy of audience behavior patterns by analyzing social media messages. Rather than directly tracking panelists through complex monitoring systems, the system copies audience engagement data from social media platforms, which provides statistically significant data at lower cost and reduced complexity
2Quantity of substance
If traditional panelist-based systems are used to collect media exposure data, then data collection is possible, but collecting statistically significant data becomes challenging across numerous distribution channels
Solution Approach 1:
The patent transitions from traditional one-dimensional panelist monitoring to a multi-dimensional approach by aggregating data across multiple social media platforms and message types. This dimensional expansion enables the system to collect statistically significant data more efficiently by leveraging the vast amount of user-generated content available across different social media ecosystems
3Productivity
If social media messages are analyzed to identify media co-relationships, then audience measurement efficiency improves, but data processing complexity increases
Solution Approach 1:
The patent segments the complex task of analyzing social media messages into distinct processing stages: data collection from multiple platforms, message filtering and cleaning, entity recognition, relationship detection, and audience estimation. This segmentation allows the system to handle large volumes of data efficiently by processing it through manageable, specialized modules
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed to identify co-relationships between media using social media. An example apparatus includes an audience estimator to: estimate a first audience of first media based on a first set of media-exposure social media messages corresponding to client devices referencing the first media, and estimate a second audience of second media based on a second set of media-exposure social media messages corresponding to the client devices referencing the second media. The example apparatus also includes a pairing classifier to: determine a pairing-score for a media-pairing based on the first and second audiences and the first and second sets of media-exposure social media messages, determine a relationship threshold to apply to the media-pairing based on the first media and the second media, and classify the media-pairing based on the pairing-score and the relationship threshold to improve an accuracy of a system associated with generating audience analysis information.