Livestreaming Data Processing for Activity Completion
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Solution Overview
Problem
Existing methods for starting preset activities in live rooms during livestreaming often result in unsatisfactory effects due to incomplete activity completion, as users may leave the live room, leading to a low success rate for bonus challenges and similar activities.
Innovation Solution
A method for processing livestreaming data that determines history contribution values of users, displays a preset object if multiple users meet a threshold, and designates a target user as the owner based on real-time contribution values, ensuring accurate and flexible display of preset objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If preset activities are started in the live room at fixed times, then the activity structure is simple and easy to operate, but the completion rate is low because users may leave the live room
Solution Approach 1:
The system dynamically adjusts the activity start time based on real-time user presence and contribution values. Instead of fixed scheduled times, the activity starts when conditions are met (enough users present with sufficient contribution values), making the system adaptive to user behavior while maintaining operational simplicity through automated condition checking.
2Stability of the object's composition
If the activity starts at scheduled time regardless of user presence, then the activity schedule is fixed and predictable, but the effectiveness is reduced due to low user participation
Solution Approach 1:
The system performs preliminary checks before starting the activity by evaluating user presence and contribution values. It accumulates contribution values in real-time and only initiates the activity when predefined conditions are satisfied, ensuring both schedule stability through predictable triggering conditions and high effectiveness through verified user participation.
3Reliability
If multiple users are required to meet threshold contribution values, then the activity requires higher user engagement, but the complexity of determining activity initiation increases
Solution Approach 1:
The system automatically monitors and accumulates contribution values from multiple users in real-time, and autonomously determines when the activity should start based on predefined thresholds. This self-service mechanism handles the complexity of multi-user condition checking without requiring manual intervention, maintaining reliability through automated enforcement of engagement requirements while keeping the operation simple for users.
Data Source
AI summary
Embodiments of the present disclosure provide a livestreaming data processing method and apparatus, and a device. The method comprises: determining historical contribution values of a plurality of users viewing first livestreaming; if the historical contribution values of at least two of the plurality of users are greater than or equal to a first threshold, displaying a preset object in a livestreaming page of the first livestreaming; obtaining real-time contribution values of the plurality of users to the first livestreaming; and if it is determined, according to the real-time contribution values of the plurality of users to the first livestreaming, that there is a target user in the plurality of users, determining an owner of the preset object as the target user, the real-time contribution value of the target user to the first livestreaming being greater than or equal to an object contribution value corresponding to the preset object.