Social Network Application Installation Broadcasting System
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Solution Overview
Problem
Users face challenges in discovering applications on various computing platforms due to the vast number of available options, even with categorization in online stores, leading to many applications going unnoticed.
Innovation Solution
A system and method that automatically publishes a user's application installation events on social networks, analyzing user activity to determine if the application should be broadcasted, composing and broadcasting messages with relevant information such as summaries, photos, videos, and ratings to the user's social networks, and suggesting applications based on friends' installations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If applications are categorized by type in online application stores, then applications are organized for easier browsing, but users still cannot easily discover applications without knowing their exact names
Solution Approach 1:
The system uses social network feedback (friends' installation events) to generate application recommendations. When a user's friend installs an application, this feedback is processed to suggest the same application to the user, creating a feedback loop that improves discovery without requiring users to know application names
Solution Approach 2:
The patent introduces social networks as an intermediary between application stores and users. Instead of direct searching, the system mediates discovery by broadcasting installation events through social networks, allowing users to discover applications through their friends' activities rather than direct store browsing
2Loss of information
If the system broadcasts all application installation events to social networks, then application visibility increases, but social network activity streams become spammed
Solution Approach 1:
The system applies different quality standards to different installation events by analyzing user activity metrics. Applications with high engagement (games, media players) are broadcast while low-engagement utilities are not, creating local quality differentiation in the broadcast content based on application importance and user interaction levels
Solution Approach 2:
The patent changes the parameter of broadcast selection from binary (broadcast all or none) to conditional based on activity analysis. By analyzing user activity patterns, ratings, and application categories, the system dynamically determines which installations meet the broadcast criterion, transforming the broadcast parameter from static to dynamic
3Object-affected harmful factors
If the system analyzes user activity to determine broadcast criteria, then spam is reduced, but system complexity increases
Solution Approach 1:
The activity analysis function is segmented into distinct components: installation event detection, activity metric collection (usage time, frequency), application categorization, and broadcast decision-making. This segmentation allows each component to handle specific tasks independently, reducing overall system complexity while maintaining comprehensive analysis
Solution Approach 2:
The system uses automatically collected user activity data from device sensors and usage logs to make broadcast decisions without requiring manual user input or configuration. The activity analyzer self-serves by continuously monitoring and processing usage patterns, eliminating the need for complex manual setup while reducing spam
Data Source
AI summary
A system and a method for notifying users of the installation of applications using social networks. An application broadcaster automatically publishes a user's application installation events on one platform to the user's activity streams on external social platforms. This way, a message regarding the application appears in the user's activity streams within social networks, resulting in the application becoming popular among the user's friends. In one embodiment, the application broadcaster determines whether user activity associated with the installed application meets a criterion before broadcasting information about the application. The application broadcaster also suggests applications that the user might find interesting.