Language Affinity Scoring for Social Network Content Feeds
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Solution Overview
Problem
Social networking services face challenges in presenting content to users in their preferred languages, leading to a heterogeneous feed that may not be optimized for individual user affinities, resulting in reduced content quality and relevance.
Innovation Solution
A method that retrieves a user's profile, identifies language features, determines a language affinity score based on user activity and profile data, and presents articles in the user's preferred language within their feed, using a scoring system that weights language features and activity data to rank and filter content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a heterogeneous feed of content in multiple languages is presented to users, then the quantity and diversity of content available increases, but the relevance and quality of content for individual users decreases
Solution Approach 1:
The patent applies local quality by customizing the content feed for each user based on their language affinity score. Instead of presenting the same heterogeneous multilingual feed to all users, the system tailors the language presentation to match individual user preferences, thereby maintaining content diversity while improving relevance for each user.
Solution Approach 2:
The system changes the language parameter of presented content based on the user's language affinity score. By calculating and applying language affinity scores, the system dynamically adjusts which language version of content is presented to each user, resolving the contradiction between maintaining multilingual content diversity and ensuring language relevance.
2Adaptability or versatility
If content is presented in multiple languages without language affinity analysis, then all users can access content in various languages, but user engagement and experience deteriorate due to language mismatch
Solution Approach 1:
The system performs preliminary action by calculating the user's language affinity score in advance, before presenting content. This pre-computation of language preference allows the system to reliably select the appropriate language version of content, thereby maintaining high user engagement while preserving multilingual accessibility.
Solution Approach 2:
The system uses feedback from user profile data and activity patterns to determine language affinity. By continuously analyzing user behavior and preferences, the system refines its understanding of each user's language preference, thereby improving engagement while maintaining accessibility to multiple languages.
3Device complexity
If a simple content filtering system is used, then system complexity remains low, but the ability to accurately determine user language preference and optimize content presentation is insufficient
Solution Approach 1:
The patent segments the language determination process into distinct components: retrieving user profile data, identifying language features, calculating language affinity scores, and selecting content based on those scores. This segmentation allows the system to achieve high measurement precision in determining language preference while keeping each individual component manageable and the overall architecture scalable.
Data Source
AI summary
The present disclosure describes various embodiments of methods, systems, and machine-readable mediums which help determine a user's likely affinity for consuming content (such as an article) in a particular language presented (or to be presented) in a heterogeneous feed of a social network.