Cognitive Social Media Post Prioritization System
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Solution Overview
Problem
Users are overwhelmed by excessive information on social media, leading to difficulties in filtering relevant content due to spam and irrelevant data, making it time-consuming to find information of interest.
Innovation Solution
A computer-implemented method and system that monitors user interactions across multiple social media accounts, learns user preferences, and cognitively prioritizes social media posts based on relevance and user goals, recommending actions such as which posts to read and when, using natural language understanding and cognitive computing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users access multiple social media accounts to find relevant information, then the variety of information sources increases, but the time required to filter and find relevant content increases significantly
Solution Approach 1:
The system automatically monitors user interactions across multiple social media accounts and autonomously prioritizes posts based on learned user preferences, eliminating the need for users to manually filter content while maintaining access to diverse information sources
Solution Approach 2:
The system dynamically changes the prioritization parameters based on learned user preferences and interaction patterns, adjusting the relevance scoring mechanism to optimize the display order of posts from multiple accounts without increasing user effort
2Measurement precision
If the system monitors and analyzes all user interactions across multiple social media accounts, then the accuracy of post prioritization improves, but the computational complexity and data processing requirements increase
Solution Approach 1:
The system extracts only the essential interaction data and user preferences needed for prioritization, filtering out redundant information while maintaining sufficient accuracy for effective post ranking
Solution Approach 2:
The system performs preliminary learning of user preferences and interaction patterns in advance, building a knowledge base that simplifies subsequent prioritization decisions and reduces real-time processing complexity
Data Source
AI summary
Disclosed is a computer-implemented method, system and program product for prioritizing social media posts and recommending action(s) to a user for the prioritized of social media posts. The computer-implemented method includes monitoring, by the data processing system, interaction(s) of a user on social media accounts of the user, receiving, by the data processing system, input from the user including information about the user and goal(s) of the user with respect to the social media accounts, learning, by the data processing system, additional information about the user, and cognitively analyzing, by the data processing system, the interaction(s) of the user, the input from the user and the additional information about the user to derive preference(s) of the user regarding the social media accounts, the preference(s) including topic(s) of relevance to the user. The computer-implemented method further includes cognitively prioritizing, by the data processing system, social media post(s) from among the social media accounts based on the topic(s) of relevance and the user preference(s), the cognitively prioritizing resulting in prioritized social media posts, and cognitively recommending action(s) to the user based on the prioritized social media posts, the topic(s) of relevance and the user preference(s).