社交人脉AI——你的领英人脉有多广？

We built SocialCraft AI to model the decay of LinkedIn connections using an exponential decay model, where relationship strength decreases by 50% every 90 days.<p>The problem we identified is that many professionals struggle to maintain meaningful connections on LinkedIn, leading to a decline in engagement and missed opportunities. For instance, if you haven&#x27;t interacted with a connection in 180 days, their relationship strength drops to just 25% of its original value. This decay can significantly impact networking effectiveness and content visibility.<p>Technically, we implemented a reciprocity ledger and engagement velocity scoring to quantify and track interactions over time. The key decision was to use an exponential decay model, which allows us to predict connection strength based on the last interaction date. This approach provides a more nuanced understanding of relationship dynamics compared to simple metrics like connection count or engagement rate.<p>What sets us apart from other social media analytics tools is our focus on the mathematical modeling of relationships rather than just surface-level engagement metrics. While tools like LinkedIn Analytics provide insights into post performance, they often overlook the underlying relationship dynamics that drive engagement. Our model helps users understand when to re-engage connections to maintain their strength.<p>Currently, we are in beta and are continuously refining our algorithms based on user feedback. Some limitations include the need for more extensive data to improve accuracy and the integration of additional social platforms beyond LinkedIn. We are also working on enhancing our content generation capabilities to better align with the engagement strategies we recommend.<p>You can try SocialCraft AI for free at https:&#x2F;&#x2F;social-craft-ai.vercel.app. We invite any technical questions or feedback on our approach!