Correlating Subjective User States with Objective Occurrences
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Solution Overview
Problem
Current social networking platforms, particularly microblogs, primarily function as open diaries for commenting and maintaining personal information, but they lack the capability to effectively correlate subjective user states with objective occurrences, limiting their use beyond mere commentary.
Innovation Solution
A computationally implemented method and system that acquires subjective user state data and solicits objective occurrence data, correlating them to determine causal relationships between subjective user states and objective occurrences, using historical data and sensor inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If social networking platforms function as open diaries for commenting and maintaining personal information, then ease of operation is improved, but the capability to correlate subjective user states with objective occurrences deteriorates
Solution Approach 1:
The system integrates multiple functions into a single platform: users can post microblog content, provide subjective state feedback, and have objective occurrence data collected and correlated automatically. This multi-functionality resolves the contradiction by enabling both ease of operation (simple posting) and analytical capability (correlation of user states with objective events) within the same system.
Solution Approach 2:
The system automatically collects objective occurrence data from various sources and correlates it with user-provided subjective state information without requiring manual intervention. This self-service approach maintains ease of operation while enabling sophisticated correlation capabilities between user states and objective events.
2Adaptability or versatility
If the system solicits objective occurrence data in response to acquiring subjective user state data, then the capability to determine causal relationships is improved, but device complexity increases
Solution Approach 1:
The system pre-establishes the framework for data collection and correlation, setting up automated processes that trigger when subjective user state data is acquired. This preliminary setup enables causal relationship determination without requiring complex real-time processing, thus managing device complexity while improving analytical capability.
Solution Approach 2:
The system introduces an intermediary correlation module that bridges subjective user state data and objective occurrence data. This intermediary component manages the complexity of correlating diverse data types while enabling the determination of causal relationships between user states and objective events.
Data Source
AI summary
A computationally implemented method includes, but is not limited to: acquiring subjective user state data including data indicating at least one subjective user state associated with a user; soliciting, in response to the acquisition of the subjective user state data, objective occurrence data including data indicating occurrence of at least one objective occurrence; acquiring the objective occurrence data; and correlating the subjective user state data with the objective occurrence data. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure.