Social Network Effectiveness Scoring via Implicit Action Segmentation
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Solution Overview
Problem
Current methods for measuring the effectiveness of social networking activities only consider explicit actions, neglecting implicit actions and failing to provide a comprehensive indication of reach and engagement, making it difficult for businesses and individuals to assess the true impact of their social media efforts.
Innovation Solution
A computer-implemented method that calculates an effectiveness score by considering both explicit and implicit actions, determining the number of unique users performing each action, and weighing these actions to provide a ratio of activity score to the number of users exposed, offering a percentage-based effectiveness score that reflects engagement and reach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only explicit actions are counted to measure social networking effectiveness, then the measurement method is simple, but the measurement precision is insufficient
Solution Approach 1:
The patent segments user actions into explicit actions (comments, shares, endorsements) and implicit actions (profile visits, content views, follow actions). This segmentation allows the system to capture both visible and hidden user interactions, thereby improving measurement precision without overwhelming complexity by organizing metrics into distinct categories that can be processed separately.
Solution Approach 2:
The patent introduces an intermediary processing layer that tracks and correlates implicit actions with explicit actions. This intermediary mechanism captures hidden user interactions (such as profile visits and content views) and integrates them with visible actions, providing a more comprehensive effectiveness measurement while managing complexity through structured data processing.
2Measurement precision
If only explicit actions are considered, then the data collection process is straightforward, but the completeness of effectiveness assessment is insufficient
Solution Approach 1:
The patent divides user interactions into two segments: explicit actions that are easily detectable through standard social media APIs, and implicit actions that require additional tracking mechanisms. This segmentation enables the system to systematically collect both types of data, improving assessment completeness while managing detection complexity through organized data collection strategies.
Solution Approach 2:
The patent implements preliminary tracking of implicit actions by setting up event listeners and tracking mechanisms before users interact with content. This preliminary action captures profile visits, content views, and follow actions as they occur, ensuring that when effectiveness assessment is performed, both explicit and implicit data are already collected and ready for analysis.
3Measurement precision
If a comprehensive measure including implicit actions is implemented, then the effectiveness indication becomes more accurate, but the processing complexity increases
Solution Approach 1:
The patent applies local quality by assigning different weights to different types of actions based on their significance. Explicit actions like shares and endorsements receive higher weights, while implicit actions like profile visits receive lower weights. This weighted approach improves effectiveness score accuracy by reflecting the varying importance of different user interactions, while managing processing complexity through a structured weighting system rather than treating all actions equally.
Solution Approach 2:
The patent changes the parameter of action weighting to reflect different levels of user engagement. By assigning numerical weights to various action types (e.g., higher weights for shares, lower weights for profile visits), the system accurately captures the relative impact of different interactions on effectiveness, while maintaining manageable complexity through consistent parameter application across all actions.
4Measurement precision
If both explicit and implicit actions are tracked, then the reach and engagement metrics improve, but the data processing requirements increase
Solution Approach 1:
The patent segments data processing into separate streams for explicit and implicit actions. This allows the system to process each type of data using appropriate methods and priorities, improving reach and engagement measurement precision while maintaining data processing efficiency by avoiding the need to process all data uniformly through a single complex pipeline.
Data Source
AI summary
A system and machine-implemented method for providing effectiveness indications for social networking activity including receiving a request to provide an effectiveness score, identifying a plurality of actions performed with respect to the social networking activity by one or more other users exposed to the social networking activity, determining the total number of unique users performing the action, calculating an activity score for the social networking activity based on the determined number of users, determining a number of the users exposed to the social networking activity, calculating an effectiveness score for the social networking activity based on the total activity score and the number of users exposed to the social networking activity, wherein the effectiveness score comprises calculating the effectiveness score at least in part based on a ratio of the activity score to the number of the users exposed to the to the social networking activity.