Emoji Ranking via Animation Compatibility in Messaging UI
Solution Overview
Problem
Existing collaborative systems, particularly on small form factor devices, face challenges with user interface designs and input mechanisms due to reduced-size input modalities, leading to sub-optimal typing experiences and inaccuracies in conveying sentiment or intent through emoji recommendations.
Innovation Solution
A messaging system with a user interface that ranks suggested emojis based on their ability to generate animation effects with the incoming emoji, prioritizing those capable of creating animated combinations, thereby enhancing contextually relevant illustrations and reducing manual input requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing content recommendation techniques are used to suggest reply emojis, then the need for manual user input is reduced, but the accuracy and granularity of conveying user sentiment or intent deteriorates
Solution Approach 1:
The system analyzes the received emoji and provides feedback by recommending reply emojis that are contextually appropriate, using the received emoji as input to generate relevant suggestions that accurately reflect user sentiment
Solution Approach 2:
The system changes the parameter of emoji recommendation from generic historical suggestions to context-specific recommendations based on the received emoji type, thereby improving accuracy while maintaining automation
2Extent of automation
If existing recommendation systems provide generic emoji suggestions based on past usage, then manual interaction is reduced, but the need for users to search through libraries to find optimal emojis increases
Solution Approach 1:
The system performs preliminary action by pre-analyzing the received emoji and preparing context-specific recommendations before the user needs to reply, thus reducing both manual interaction and search time
Solution Approach 2:
The system acts as an intermediary between the received emoji and the user's reply by providing curated suggestions that bridge the gap between generic recommendations and the user's intent, eliminating the need to search entire libraries
3Measurement precision
If complex interactions are required to locate and select correct emojis, then precision in conveying intent is improved, but the number of inadvertent inputs and unnecessary interactions increases
Solution Approach 1:
The system applies local quality by providing targeted emoji suggestions specifically relevant to the received emoji context, ensuring high precision while requiring minimal user interaction to select from relevant options
Data Source
AI summary
The disclosed techniques provide a messaging system with a user interface (UI) having a specific arrangement of suggested expressive illustrations, such as emojis. In some examples, a system analyzes a received emoji and provides a suggested list of emojis for a response. The suggested emojis are arranged in a way that candidate emojis capable of generating animation effects in combination with the received emoji, are listed higher in ranking, e.g., preceding, over other candidate emojis that cannot generate animation effects in combination with the received emoji. The system can rank individual emojis, or other types of graphical expressions, depending on whether a candidate emoji is capable of generating animated effects with the received emoji. In some embodiments, candidate emojis that are capable of generating animated effects precede candidate emojis that are incapable of generating animated effects.