Location-Driven Social Network Augmentation for Travel
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Solution Overview
Problem
Existing social networks are ineffective when users travel outside their regional focus, lacking means to automatically boost their network at a destined location for support such as recommendations for restaurants, hotels, and rental cars.
Innovation Solution
A method and system that detects a user's travel or intent to travel, generating a network graph and identifying gaps in their social network at the destination, then augments the network to fill these gaps by connecting users with relevant expertise or experience at the new location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users rely on their existing social network connections, then they have strong regional support and familiar contacts, but they lack access to local resources and expertise when traveling to new locations
Solution Approach 1:
The system proactively detects travel intent before the user arrives at the destination and automatically begins augmenting their social network with relevant local connections. This preliminary action ensures the user has access to local expertise before they actually need it, resolving the contradiction by preparing the network in advance rather than waiting for the user to manually seek connections.
Solution Approach 2:
The system automatically performs network augmentation without requiring manual intervention from the user. It self-services by detecting travel intent, identifying appropriate local connections, and establishing network bridges autonomously. This resolves the contradiction by making the system work automatically rather than requiring the user to actively manage their network while traveling.
2Adaptability or versatility
If the social network remains focused on the user's home region, then existing connections are maintained, but the network becomes ineffective for obtaining local support at travel destinations
Solution Approach 1:
The system segments the social network into location-specific components, creating separate network graphs for the user's home region and travel destination. This allows the network to maintain strong home region connections while simultaneously establishing reliable local connections at the destination, resolving the contradiction by treating different locations as separate network segments rather than a single unified network.
Solution Approach 2:
The system introduces an intermediary travel detection and network augmentation mechanism that bridges the user's home network and destination network. This intermediary component detects travel intent and automatically creates connections between the user and local contacts at the destination, ensuring reliable local support without abandoning home region connections.
3Adaptability or versatility
If manual network management is required when traveling, then users can curate their own connections, but the process is time-consuming and complex
Solution Approach 1:
The system automatically manages network augmentation by detecting travel intent, identifying relevant local connections, and establishing network bridges without user intervention. This self-service approach resolves the contradiction by eliminating the need for manual network management while still providing customized local connections tailored to the user's travel needs.
Solution Approach 2:
The system continuously monitors user location and travel intent, using this feedback to automatically adjust and augment the social network with appropriate local connections. This feedback loop resolves the contradiction by making the network adaptive to user needs without requiring manual configuration, as the system automatically responds to changes in user context.
Data Source
AI summary
A method, a structure, and a computer system for location-driven social network boosting. The exemplary embodiments may include generating a network graph corresponding to a user of a social network and identifying a destined location of the user that differs from a current location of the user. The exemplary embodiments may further include identifying one or more gaps in the social network of the user at the destined location and augmenting the social network to fill the one or more gaps at the destined location.