Topic-Specific Influence Score Determination for Social Communities

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Existing social media analysis technologies fail to accurately attribute viral growth to specific individuals or groups, limiting targeted advertising and influence measurement across diverse topics and communities.

Innovation Solution

A method to determine an influence score by evaluating the reach and quality of communications within a community, comparing user interactions, and storing scores for targeted advertising and content propagation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If existing social media analysis technologies are used to measure user impact, then general influence scores can be obtained, but accurate attribution of viral growth to specific individuals or groups cannot be achieved

Engineering Contradiction:
Improveinfluence measurement accuracyVSAvoidviral growth attribution information
Core Design Contradiction:
Measurement precisionVSLoss of information

Solution Approach 1:

The patent segments the influence measurement by creating topic-specific influence scores for different communities rather than using a single general influence score. This segmentation allows the system to accurately attribute viral growth to specific individuals within particular topic contexts, resolving the contradiction between general measurement capability and specific attribution precision.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by evaluating user influence within specific communities and topics rather than applying a uniform measurement across all social media interactions. This localized approach enables accurate identification of key influencers for targeted advertising campaigns while preserving the nuanced information about where and how viral growth occurs.

Inventive Principle:
Principle #3Local quality

2Productivity

If general influence scores are calculated without topic and community context, then computation is simpler, but targeted advertising and content propagation effectiveness is reduced

Engineering Contradiction:
Improveadvertising campaign effectivenessVSAvoidinfluence score calculation complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The system segments influence calculation into multiple topic-specific and community-specific scores, which initially appears to increase complexity. However, this segmentation enables highly targeted advertising campaigns that are much more effective, as advertisers can identify precisely which influencers to engage with for specific topics and communities, thereby improving productivity despite the increased calculation complexity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent creates a multi-functional influence scoring system that can be applied across multiple topics and communities simultaneously. Once the framework is established, it can evaluate user influence for any combination of topics and communities, making the system universally applicable and efficient for diverse advertising campaigns while maintaining manageable complexity through reusable evaluation metrics.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS9632972B1Determining influence in a social community
Publication Date: 2017.04.25 GOOGLE LLC
  • US9632972B1 patent drawing
  • US9632972B1 patent drawing
  • US9632972B1 patent drawing

AI summary

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining influence in a social community. In one aspect, a method includes identifying a user in a community; determining an influence score to be associated with the user in the community for a particular topic, including: determining a reach of one or more communications that relate to the particular topic that have been distributed from the user to other users in the community, and evaluating the reach as compared to the reach of one or more communications distributed from other users in the community for the particular topic; and storing the influence score in association with the user.