Dynamic User Image Motion for Sentiment-Driven Social Engagement
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Solution Overview
Problem
Existing social networking services fail to engage users when the sentiment analysis of input sentences is not accurately identified, leading to uninteresting experiences.
Innovation Solution
A message-browsing system that includes an image storage unit, motion storage unit, keyword storage unit, determination unit, and setting unit to analyze and respond to user posts with dynamic user images and motions based on sentiment and post forms, ensuring user engagement even if sentiment identification is not possible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If sentiment analysis is used to change image expressions, then user engagement is improved when sentiment is accurately identified, but user engagement deteriorates when sentiment cannot be identified
Solution Approach 1:
The system pre-prepares multiple motion information pieces corresponding to different post forms (text post, image post, video post) and stores them in the motion storage unit. When sentiment analysis fails to identify a type, the setting unit automatically selects appropriate motion information based on the post form category, ensuring continuous user engagement without interruption due to analysis failure.
Solution Approach 2:
The determination unit acts as an intermediary between the sentiment analysis process and the motion selection process. It determines whether sentiment analysis has successfully identified a sentiment type, and based on this determination, directs the setting unit to either select motion information based on sentiment (when identified) or based on post form (when not identified), thus mediating the transition between different selection strategies.
2Ease of operation
If multiple motion information pieces are stored for different sentiments and post forms, then user interest is maintained through dynamic image changes, but system complexity increases
Solution Approach 1:
The motion information storage is segmented into multiple distinct pieces, each corresponding to specific combinations of sentiment types and post forms. The determination unit segments the decision-making process into two paths: one for when sentiment is identified and another for when it is not. This segmentation allows the system to manage complexity by organizing motion information in a structured, categorized manner rather than using a single undifferentiated storage approach.
Solution Approach 2:
The setting unit dynamically selects motion information based on real-time conditions: it first checks whether sentiment analysis has identified a sentiment type, then selects from motion information corresponding to either the identified sentiment or the post form. This dynamic selection mechanism allows the system to adapt to different scenarios without requiring a fixed, overly complex structure, as the complexity is managed through conditional logic rather than hard-coded pathways.
Data Source
AI summary
A message-browsing system includes an image storage unit storing user images corresponding to respective multiple users, a motion storage unit storing pieces of motion information defining motions of the images associated with types of feelings or forms of posts, a keyword storage unit storing keywords according to the types of feelings, a determination unit determining whether or not any of the types can be identified from a sentence of a post by determining whether the sentence includes any of the keywords stored in the keyword storage unit, and a setting unit, when a type of feelings can be identified, selecting one of pieces of motion information that corresponds to the identified type of feelings, selecting one piece of motion information that corresponds to a form of the post when the type cannot be identified, and setting a motion of a user image corresponding to the user who has contributed the post based on the selected piece of motion information.