Social Feed Translation via Segmentation and Intermediary Mediation
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Solution Overview
Problem
Current online social platforms lack the ability to support intra-community communication effectively, as they do not adapt feed items to the specific posting formats of each destination social environment, leading to inconsistent user experiences across different platforms.
Innovation Solution
The technology creates separate instances of a feed item, each compatible with the unique tag formats and social handles of the destination online social environments, allowing for seamless embedding and cross-posting across multiple platforms while preserving the original formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If feed items are posted across multiple online social environments, then the quantity of social networks supported increases, but the compatibility with each specific platform's posting format deteriorates
Solution Approach 1:
The feed item is divided into separate instances, with each instance tailored to a specific destination online social environment. Each instance contains platform-specific entity mention translations and formatting, allowing the system to maintain both multi-platform support and precise format compatibility simultaneously
Solution Approach 2:
Each instance of the feed item is customized with local quality specific to its destination platform, including platform-specific entity mention formats, tag styles, and identifier conventions. This ensures that while the overall system supports multiple platforms, each individual feed item instance is optimized for its specific target platform
2Adaptability or versatility
If separate instances of feed items are created for different social environments, then the adaptability to platform formats improves, but the device complexity increases
Solution Approach 1:
An intermediary system is introduced between the source feed item and multiple destination platforms. This intermediary automatically translates entity mentions, selects appropriate platform-specific formats, and manages the creation of separate instances for each destination platform, reducing the complexity of manual platform-specific content creation
Solution Approach 2:
The system automatically changes key parameters of the feed item instances based on the destination platform, such as entity mention formatting, tag styles, and identifier conventions. By parameterizing these changes rather than creating entirely separate content structures, the system manages complexity while maintaining platform-specific adaptability
3Ease of operation
If entity mentions are translated to platform-specific formats, then the user experience on each platform improves, but the loss of original format information increases
Solution Approach 1:
The system creates separate instances for each destination platform, allowing the original feed item and its format information to be preserved in the source while generating platform-specific translations for each instance. This segmentation prevents information loss by maintaining the original as a reference while creating adapted versions for each platform
Data Source
AI summary
The technology disclosed relates to adapting online social feed items according to the posting formats of each of the multiple destination online social environments to which they are posted, regardless of the source online social environments from which they originate. In particular, it relates to creating separate instances of a feed item such that each of the instances includes tag formats, social handles or identifiers that are compatible to the online social environments in which they are embedded. These separate instances of a feed item can all be embedded in a first online social environment while preserving their tag formats corresponding to other online social environments.