Social Graph Context Provision via Activity-Based Notification
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Solution Overview
Problem
Social graph additions in social networks often lack context, leaving secondary users unaware of the primary user's motivations or reasons for adding them, which can lead to unclear intentions and misunderstandings.
Innovation Solution
A method and system that provide context to secondary users by processing requests to add them to a primary user's social graph, determining the context based on the secondary user's activities on network-accessible properties, and generating a message with information about the context, allowing the secondary user to understand the primary user's motive for the addition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a user is added to another user's social graph without providing context, then the social graph addition mechanism is simple and fast, but the secondary user lacks understanding of the primary user's motivations leading to unclear intentions
Solution Approach 1:
The system performs preliminary actions by automatically determining context information about the secondary user's activities before generating the notification message. This includes querying activity data from network-accessible properties and preparing context descriptions in advance, so that when the social graph addition occurs, the contextual information is already ready to be provided to the secondary user.
Solution Approach 2:
The system introduces an intermediary context information layer between the primary user's addition action and the secondary user's reception. This intermediary component automatically generates and inserts contextual descriptions (such as activity-based context) into the notification message, mediating the information flow and providing meaningful context without requiring direct communication between users.
2Reliability
If context information is provided to secondary users about social graph additions, then user understanding and clarity improve, but the processing time and computational resources increase
Solution Approach 1:
The system changes parameters by selectively determining context information based on the specific activity type and relevance. Rather than providing all possible context data uniformly, the system adjusts the level and type of context provided according to the activity characteristics, optimizing the balance between user understanding and processing efficiency.
Solution Approach 2:
The system applies partial action by determining only the most relevant context information needed for user understanding, rather than comprehensively analyzing all possible activity data. This selective approach provides sufficient context for clarity while avoiding unnecessary processing overhead.
Data Source
AI summary
In one aspect, a method for providing context regarding an addition to a social graph is provided. The method initiates with processing a request from a first user to add a second user to a social graph of the first user. A context that identified the second user to the first user is identified, the context defined by an activity of the second user preceding the request to add the second user to the social graph of the first user. A message is generated for the second user describing the processed request and containing information based on the context that identified the second user to the first user.