Message Digest System for Social Networking
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Solution Overview
Problem
Members of online social networking services are overwhelmed by excessive messages, leading to uninformed status due to either too few or too many messages, causing important messages to be missed.
Innovation Solution
A system determines a message transmission frequency threshold for each member based on their responses, storing messages in a digest when the threshold is exceeded and transmitting them when a send score is reached, prioritizing messages from prominent individuals and adjusting based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system transmits more messages to members, then the completeness of information delivery is improved, but the member becomes overwhelmed and annoyed, reducing engagement
Solution Approach 1:
The system dynamically changes the parameter of message transmission frequency based on individual member thresholds. Each member has a determined threshold beyond which they become overwhelmed, and the system adjusts transmission frequency to stay below this threshold while maximizing information delivery. This resolves the contradiction by finding the optimal parameter value that balances completeness with user experience.
Solution Approach 2:
The system uses member responses (positive or negative) as feedback to determine message transmission frequency thresholds. When members respond negatively to message frequency, the system learns and adjusts the threshold downward. This feedback loop enables the system to adapt to individual member preferences, delivering complete information without causing annoyance.
2Object-affected harmful factors
If the system transmits fewer messages to members, then member annoyance is reduced, but important messages may be missed
Solution Approach 1:
The system applies different transmission strategies to different members based on their individual characteristics and thresholds. Each member receives a customized message frequency tailored to their specific tolerance level, rather than a uniform approach. This local quality adaptation ensures that each member receives the maximum appropriate number of messages without annoyance, preventing important messages from being missed.
Solution Approach 2:
The message transmission frequency is not static but dynamically adjusted based on member responses and determined thresholds. The system continuously learns from member interactions and adapts the transmission rate accordingly, enabling it to optimize the balance between reducing annoyance and ensuring important messages are delivered.
3Measurement precision
If the system determines individual message thresholds for each member, then message delivery precision is improved, but system complexity increases
Solution Approach 1:
The system determines message thresholds through member responses rather than requiring complex manual configuration. Members effectively self-service the threshold determination by providing feedback (positive or negative responses) that the system uses to learn their preferences. This approach achieves high measurement precision while minimizing system complexity, as the threshold is emergent from member behavior rather than requiring complex algorithms or manual setup.
Data Source
AI summary
This disclosure relates to systems and methods for managing multiple messages. In one example, a method includes determining a message transmission frequency threshold for a member of an online social networking service using responses from the member; receiving a message that is to be transmitted to the member; storing the message, without transmitting the message to the member, in a digest of messages for the member; and transmitting the digest to the member in response to a send score for the digest exceeding a send score threshold, the send score calculated using the number of messages in the digest.