Social Network Message Discoverability via Trending Keyword Integration
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Solution Overview
Problem
Social media messages often fail to reach the intended audience, resulting in low response rates due to lack of discoverability, as they are not optimized for the target group's attention.
Innovation Solution
A computer-implemented method that detects messages requesting a response, searches the social network for relevant search terms, ranks them by usage, and allows users to substitute or append these terms to enhance message discoverability, thereby increasing the likelihood of reaching the intended audience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users post messages on social networks without optimization, then the posting process is simple and quick, but the messages are not discovered by the intended audience resulting in low response rates
Solution Approach 1:
The system performs preliminary actions by automatically analyzing the user's draft message, identifying relevant keywords, searching for trending topics and hashtags, and generating optimization suggestions before the user posts the message. This allows users to benefit from optimized messaging without manually performing the complex analysis and research work.
Solution Approach 2:
The system enables self-service by providing users with automated tools that analyze their own messages, suggest improvements, and help them optimize content independently. Users can review suggestions and make decisions about which optimizations to apply, maintaining control while benefiting from automated analysis.
2Productivity
If users manually research and optimize messages for discoverability, then message discoverability improves, but the time and effort required to compose messages increases
Solution Approach 1:
The system replaces the manual mechanical process of researching keywords, trends, and hashtags with an automated computational system. The system uses algorithms to analyze messages, search for relevant trends, and generate optimization suggestions, substituting human manual research with automated digital analysis.
Solution Approach 2:
The system acts as an intermediary between the user's draft message and the social network platform. It analyzes the message content, bridges the gap by finding relevant trending topics and hashtags, and provides suggestions that connect the user's intent with current platform trends, thereby improving discoverability without direct manual intervention.
3Productivity
If messages use generic terms, then the message is easy to write, but the message does not reach the appropriate target audience
Solution Approach 1:
The system applies local quality by analyzing specific portions of the message (keywords, phrases) and providing targeted optimization suggestions for those specific areas. Rather than requiring complete rewriting, it suggests localized improvements to specific terms and phrases that will enhance audience targeting while preserving the overall message structure and user's writing style.
Data Source
AI summary
A method, system and computer program product for improving the discoverability of messages on a social network. The creation of a proposed message that requests a response from a target audience is detected. The social network is then searched to identify search terms and posts related to the proposed message. Upon identifying the search terms, the search terms are ranked in order of usage among the identified posts. A list of identified search terms in order of rank is then presented to the user to modify the proposed message. The proposed message is modified using a search term selected by the user from the list of search terms. The modified message is then posted on the social network. In this manner, the message created by the user has been modified to improve the discoverability of the message on the social network and to increase responses from an appropriate target audience.