Meme Detection Engine for Social Chatter Analysis
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Solution Overview
Problem
Existing machine intelligence systems face challenges in analyzing diverse human conversations due to variations in languages and conversationalists, making it difficult to provide insights from a broad collection of digital chatter.
Innovation Solution
A concept study system incorporating a meme analysis engine that utilizes a super topic taxonomy to filter and analyze user-generated content, identifying key terms and memes across different groups by segmenting conversations and applying relevance ranking engines for linguistic and absolute relevancy metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If machine intelligence systems analyze diverse human conversations, then insights from digital chatter can be obtained, but variations in languages and conversationalists make analysis difficult
Solution Approach 1:
The patent segments the diverse digital chatter into distinct meme groups based on linguistic patterns, topics, and conversational characteristics. By dividing the heterogeneous data into manageable segments, the system can apply specialized analysis to each group while maintaining overall adaptability to diversity in languages and conversationalists
Solution Approach 2:
The patent creates a universal meme detection framework that can handle multiple languages and conversation types through a single system architecture. The meme analysis engine is designed to be multi-functional, adapting to different linguistic patterns and conversational styles while maintaining a consistent analysis approach across diverse inputs
2Productivity
If meme analysis engine processes large quantity of user-generated content, then insights into user interests and trends can be provided, but real-time analysis of extensive digital chatter remains challenging
Solution Approach 1:
The patent implements preliminary action by pre-processing user-generated content to identify and segment memes before full analysis. The system performs initial filtering, categorization, and pattern recognition on incoming chatter, preparing the data in advance for more efficient detailed analysis. This preliminary processing reduces the time required for comprehensive meme detection and insight generation
Solution Approach 2:
The patent replaces traditional mechanical text analysis methods with advanced machine learning-based meme detection algorithms. The system uses computational models to automatically identify linguistic patterns, topics, and conversational memes, substituting manual or rule-based analysis with intelligent automated processing that handles large volumes of content more efficiently
Data Source
AI summary
Some embodiments include a method of detecting memes, as “key terms,” in a chatter aggregation in a social networking system. The method can include aggregating user-generated content objects within the social networking system into the chatter aggregation according to a set of filters. A meme analysis engine can define a target group within the chatter aggregation to compare against a background group. The meme analysis engine can extract key terms from textual content of the target group. The meme analysis engine can determine a relevancy rank of a term in the key terms based on an accounting of the term in the textual content of the target group and a linguistic relevance score of the term according to a linguistic model.