Key-Author Search Module for Social Network Content
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Solution Overview
Problem
Social networking systems face challenges in efficiently identifying and retrieving relevant content and key authors associated with specific topics within their vast networks, as existing search methods often fail to accurately filter and prioritize information.
Innovation Solution
The system receives a search query, identifies key authors by crawling third-party systems and extracting candidate names from objects associated with the topic, assigns author scores based on relevance, and generates search results modules that include references to objects authored by key authors, prioritizing those with high scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system searches through all objects in the social network to find relevant content, then the completeness of search results is improved, but the search time and computational resources increase significantly
Solution Approach 1:
The system pre-identifies and stores key-authors associated with various topics before search queries are executed. This preliminary action creates an indexed structure of topic-author relationships that enables rapid retrieval during search operations, eliminating the need to scan all objects in the social network for each query while maintaining complete and accurate results.
2Measurement precision
If the system retrieves all objects authored by potential key-authors, then the accuracy of identifying relevant content is improved, but the quantity of retrieved data increases, requiring more processing resources
Solution Approach 1:
The system extracts and isolates only the essential attribute needed for search accuracy - the author-score metric that quantifies key-author relevance. By extracting this specific scoring mechanism and applying it to filter retrieved objects, the system maintains high accuracy in identifying relevant content while reducing the volume of data that requires detailed processing, as low-scoring objects can be efficiently filtered out.
3Adaptability or versatility
If the system uses multiple search-results modules to organize content by different criteria, then the versatility of search results is improved, but the complexity of the search system increases
Solution Approach 1:
The search system is segmented into distinct functional modules: a key-author identification module that pre-processes author information, and multiple search-results modules that can be independently configured to present results according to different criteria (e.g., by author, by topic, by recency). This segmentation allows each module to perform a specific function with simple logic, while the combination provides versatile search capabilities, reducing overall system complexity through functional decomposition.
Data Source
AI summary
In one embodiment, a method includes receiving, from a client device of a first user of an online social network, a search query associated with a first topic. The method also includes identifying one or more key-authors associated with the first topic. The method further includes retrieving multiple objects of the online social network matching the search query, where one or more of the retrieved objects are associated with the first topic and are authored by at least one of the identified key-authors. The method also includes generating multiple search-results modules, each search-result module including references to one or more of the retrieved objects. At least one of the search-results modules is a key-authors-module that includes references to one or more of the retrieved objects associated with the first topic that are authored by at least one of the identified key-authors.