Social Media Image Appeal Prediction System

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Solution Overview

Problem

There is no known system for evaluating images intended to be posted to social media platforms, which makes it difficult for users to predict the appeal of their images and garner reactions from other users.

Innovation Solution

An information processing system that includes a type acquisition unit, a count acquisition unit, and a prediction unit to predict the evaluation of an image based on its type and reaction data from social media platforms, also considering follower counts for potential reactions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If users capture multiple photographs as candidates and carefully select images for posting, then the image appeal and potential reactions are improved, but the time consumption and operational complexity increase

Engineering Contradiction:

Improveimage appeal prediction accuracyVSAvoidtime for image selection and evaluation

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary evaluation of images before they are posted to social media. The prediction unit pre-calculates the likely reaction count for each candidate image based on its type and the user's follower count, allowing users to select images in advance without needing to capture and evaluate multiple photos during the moment of posting

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system enables self-service evaluation by automatically predicting image appeal metrics. Instead of requiring users to manually evaluate multiple photographs or ask friends for opinions, the prediction unit autonomously assesses each image's potential reaction count based on machine learning models, providing immediate feedback without human intervention

Inventive Principle:

Principle #25Self-service

2Measurement precision

If users ask friends to evaluate which photographic image is appealing, then the evaluation accuracy is improved, but the device complexity and operational burden increase

Engineering Contradiction:

Improveimage evaluation accuracyVSAvoidsystem complexity for image evaluation

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system replaces the mechanical process of human evaluation (asking friends to review images) with an automated computational system. The prediction unit uses machine learning models to calculate predicted reaction counts for each image, substituting human judgment with algorithmic assessment that provides consistent, objective, and immediate results

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The prediction unit acts as an intermediary between the user's images and the social media platform. Instead of directly posting images and waiting for friend reactions, the system inserts a prediction layer that analyzes image types and calculates potential reaction counts, providing evaluated results before the actual posting occurs

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11651280B2Recording medium, information processing system, and information processing method

Publication Date: 2023.05.16 MICWARE CO LTD

AI summary

The present disclosure provides an information processing system for predicting an evaluation of an image that is to be posted to a social media platform, and methods of use thereof.