Social Network Reference Search and Filtering
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Solution Overview
Problem
Current social networking systems lack efficient tools for making better human network connections on the Internet, particularly in finding suitable referrals and managing relationships, as they do not effectively integrate digital communications with the knowledge contained in aggregate contacts, leading to inefficient decision-making processes.
Innovation Solution
The development of advanced filtering, searching, and reference checking tools within social networking applications, including a 'one-click' reference search feature, viral forwarding of searches, and enhanced message management functions to prioritize and filter messages based on user-definable criteria, allowing users to access and utilize their network connections more effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated means are used to assist in decision-making processes regarding human networks, then efficiency is improved, but the ability to form relationships or introductions among members of disparate human networks is not achieved
Solution Approach 1:
The patent introduces a social networking system that acts as an intermediary between disparate human networks. The system includes a server that maintains a database of user profiles and enables users to search for and connect with individuals outside their immediate networks. The server mediates introductions and reference checks, allowing automated efficiency while simultaneously enabling relationship formation across network boundaries.
Solution Approach 2:
The social networking system performs multiple functions: it serves as a database for profile storage, a search engine for finding contacts, a communication platform for introductions, and a reference checking system. This multi-functionality allows a single automated system to both improve efficiency and enable relationship formation across diverse networks.
2Reliability
If referrals are made within personal networks, then trust is maintained, but the reach is limited by the size of the individual's network
Solution Approach 1:
The patent extends the traditional two-dimensional personal network by adding a third dimension through the social networking system. Users can access and search profiles beyond their direct connections, effectively adding depth and breadth to their network reach while maintaining the trust framework through systematic reference checking and profile verification features.
Solution Approach 2:
The system incorporates reference checking mechanisms where users can verify the credibility of individuals outside their immediate networks. This feedback loop maintains trust by allowing users to assess the reliability of new connections before engaging, thus extending network reach without sacrificing trust standards.
3Reliability
If multiple leads are tracked to find suitable candidates, then the chances of finding a suitable target increase, but the process becomes inefficient and time-consuming
Solution Approach 1:
The system performs preliminary actions by maintaining detailed profiles that include references, skills, and background information before actual referrals are needed. When a user searches for a candidate, the system can immediately filter and rank based on pre-collected data, eliminating the need to track down multiple leads manually and significantly reducing the time to find suitable candidates while maintaining reliability through comprehensive pre-verification.
Data Source
AI summary
A computer-implemented method for identifying a potential reference is disclosed. In one embodiment, a user interface (UI) object (e.g., a one-click reference search button) is provided, for example, on a web page displayed at a user's client device. When selected, the UI object causes a reference search query to be generated. The search query identifies the user performing the search, and a target person for whom the user would like a reference. The search query is communicated to, and processed by, a social networking system (e.g., through an API function call). In turn, the social networking system returns information about potential references to the client.