Breakout Prediction via Web Data Mining and Logarithmic Scoring
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Solution Overview
Problem
Current methods for predicting breakout success in media, such as music or film, rely heavily on human insights and are not scalable for large media catalogs without technological assistance, making it difficult to consistently and objectively identify emerging artists and content.
Innovation Solution
An automated system that scrapes web content, transforms unstructured data into structured data, clusters web pages, counts headline mentions and consumer interactions, and calculates a 'breakout value' using logarithmic formulas to predict potential success across entire media catalogs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human insights and editorial content are used to predict breakout success, then prediction accuracy is improved, but scalability to large media catalogs deteriorates
Solution Approach 1:
The patent replaces manual human analysis of editorial content with automated text mining and natural language processing systems. The system systematically extracts insights from web pages, news articles, and editorial content using computational methods, enabling scalable application across large media catalogs while maintaining prediction accuracy through consistent objective analysis
Solution Approach 2:
The system enables media catalogs to self-evaluate breakout potential through automated analysis. By implementing self-service capabilities where the system independently processes and analyzes editorial content without human intervention, scalability is achieved while maintaining consistent prediction methodology across all media items
2Quantity of substance
If human insights are applied to large media catalogs, then comprehensive coverage is improved, but consistency and objectivity deteriorate
Solution Approach 1:
The patent replaces subjective human judgment with objective computational analysis. The system uses standardized text mining algorithms and natural language processing to consistently evaluate editorial content across all media items, eliminating variability in human assessment while maintaining comprehensive catalog coverage
Solution Approach 2:
The system transforms unstructured editorial content into structured quantitative metrics through systematic parameter extraction. By converting qualitative insights into measurable parameters such as sentiment scores, mention frequency, and editorial impact metrics, the system achieves both comprehensive coverage and consistent objective evaluation across the entire catalog
3Productivity
If technology is used to analyze editorial content, then scalability is improved, but complexity of the system deteriorates
Solution Approach 1:
The patent divides the complex task of breakout prediction into distinct modular components: web scraping modules, text mining modules, natural language processing modules, and prediction algorithms. Each module handles a specific aspect of the analysis independently, making the overall system more manageable and scalable while reducing the complexity burden on any single component
Data Source
AI summary
Methods, systems and computer program products for using a selected cohort of content consumers to rate a media object is provided by identifying a media object, determining a first value, where the first value is equal to a number of content consumers who belong to a cohort and who have played the media object, determining a second value. The second value is equal to a total number of content consumers who played the media object. A rating is computed using the first value and the second value.