User Translation Selection in Social Networks
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Solution Overview
Problem
Social networking systems face challenges in providing accurate translations due to language barriers, as users may provide faulty translations intentionally or unintentionally, and it is impractical for the system to provide official translations for all languages.
Innovation Solution
A translation module determines user qualifications based on language competencies and trustworthiness, and a selection module chooses the most appropriate translation for users by evaluating factors such as translation quality and user similarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users are allowed to provide translations of postings, then the system can provide translations for multiple languages without official translations, but the translations may be faulty or misleading
Solution Approach 1:
The system implements a feedback mechanism where translations provided by users are evaluated by other users and the system. High-quality translations receive positive feedback and are selected for display, while poor translations are rejected. This creates a self-improving system where translation quality increases over time through continuous evaluation and selection.
Solution Approach 2:
The system enables users to translate content themselves rather than relying on official translations. Users can provide translations for postings in languages they understand, allowing the system to automatically serve translations for multiple languages without requiring official translation resources for each language pair.
2Reliability
If the system evaluates user qualifications and translation quality, then translation reliability improves, but system complexity increases
Solution Approach 1:
The evaluation system leverages the community itself to perform the evaluation work. Other users rate and evaluate translations provided by their peers, eliminating the need for a complex automated evaluation system. The system simply collects and processes user feedback, making the complexity distributed across the user base rather than centralized in the system.
3Measurement precision
If multiple translations are evaluated and selected, then users receive higher quality translations, but processing time increases
Solution Approach 1:
The system pre-evaluates and caches translation quality metrics in advance. When a translation is submitted, it undergoes evaluation and the results are stored. When the same or similar translation is needed again, the pre-evaluated translation can be quickly retrieved and selected without repeating the full evaluation process, significantly reducing processing time for subsequent selections.
Data Source
AI summary
A social networking system determines whether a particular user is qualified to provide translations of text from a first language to a second language. The determination may include evaluation of the language competencies of the user, and also of the trustworthiness of the user as a translator, as determined based on prior translations submitted by the user. The social networking system also selects translations of a text item for a user to whom that text is to be shown. When evaluating a candidate translation for presentation to the user, the evaluation may assess factors such as the determined qualification as a translator of the user who provided the candidate translation; a quality score of the candidate translation itself; and/or the similarity of the user viewing the content and the user providing the candidate translation.