Trending Content Analysis System for Timely Popularity Detection
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Solution Overview
Problem
Existing services for measuring the popularity of web sites, web pages, and topics are not sufficiently reliable or timely in indicating currently trending content items.
Innovation Solution
A system that analyzes content requests from multiple client devices to identify trending content characteristics, such as topics, and generates reports or data feeds summarizing these trends, allowing content servers to tailor their content based on popular and trending characteristics, including demographic data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing services use various sources of behavioral data (search engine traffic, blog posts, Twitter posts) to measure popularity, then they can provide some indication of popular topics, but they do not provide sufficiently reliable and timely indication of currently trending content items
Solution Approach 1:
The patent segments the analysis into two distinct components: popularity measurement (based on absolute request counts) and trend detection (based on rate of change). This segmentation allows the system to use different data sources and analysis methods for each function, improving both reliability and timeliness without compromising either metric.
Solution Approach 2:
The patent introduces an intermediary analysis layer that processes raw content request data between the data collection phase and the final popularity/trend reporting. This intermediary layer applies sophisticated algorithms to filter noise, detect patterns, and generate reliable trend indicators, resolving the contradiction between using multiple data sources and achieving timely, accurate results.
2Measurement precision
If content servers want to accurately identify trending content characteristics to tailor their content offerings, then they need comprehensive analysis of content requests, but this requires processing and analyzing large volumes of data from multiple client devices
Solution Approach 1:
The patent performs preliminary actions by pre-processing and categorizing content requests as they are received, organizing data by content characteristics before the actual trend analysis begins. This preliminary organization reduces the complexity of subsequent analysis while maintaining measurement precision, as the data is already structured for efficient processing.
Solution Approach 2:
The system implements self-service mechanisms where the analysis framework automatically adapts to different content types and request patterns without requiring manual configuration. The system self-calibrates its analysis parameters based on the incoming data characteristics, reducing the operational complexity while maintaining high measurement precision for trend identification.
Data Source
AI summary
Features are disclosed for analyzing requests for network accessible content, including but not limited to web pages, to determine which topics and other characteristics are popular or are gaining in popularity (“trending”). Content items or sources may be profiled to determine characteristics that two or more content items or sources may have in common. Content requests from multiple client devices may be tracked and analyzed to determine the trending or popular characteristics. Data feeds or reports regarding the summarized content requests may be generated and distributed to content servers and other entities. The data feeds may be used to tailor content, such as by highlighting or featuring content associated with the most-requested content characteristics, or utilizing demographic data to tailor content for different users.