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我一直在思考新市场叙事是如何形成的。不是那些大家已经在讨论的显而易见的叙事，而是早期阶段——当一个主题或股票代码悄然开始在讨论中越来越多地出现，直到它变得主流。大多数交易工具关注的是价格、指标或信号。但市场往往是因为关注度和叙事先建立起来才会发生变化。因此，我一直在尝试一个小系统，试图跟踪以下内容： • 股票提及的突然增加 • 讨论一个主题的独立参与者数量 • 讨论是否在多个时间窗口中持续存在 • 一个叙事周围的关注度增长速度这个系统的目标不是生成买入/卖出信号，而是理解市场关注度如何随时间演变。最近，我还在探索一些想法，比如： • 叙事阶段（出现 → 扩展 → 顶峰 → 衰退） • 不同社区之间的关注度持续性 • 关注度的变化是否往往会先于价格变动这个项目目前是一个不断发展的研究工具，我们称之为MindQuant AI。我们的想法是，理解市场的工具不应该是静态的——因为市场中的叙事和行为是不断变化的。所以我很好奇其他人对此的看法。如果你在构建一个市场情报系统，你希望它跟踪哪些信号？

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I’ve been thinking a lot about how new market narratives form.Not the obvious ones everyone already talks about, but the early stage - when a theme or ticker quietly starts appearing more and more in discussions before it becomes mainstream.Most trading tools focus on price, indicators, or signals. But markets often move because attention and narratives build first.So I’ve been experimenting with a small system that tries to track things like: • sudden increases in ticker mentions • how many unique participants are discussing a theme • whether discussions persist across multiple time windows • how quickly attention around a narrative growsThe goal isn’t to generate buy/sell signals, but to understand how market attention evolves over time.Recently I’ve also been exploring ideas like: • narrative phases (emerging → expanding → peak → fading) • attention persistence across communities • whether shifts in attention tend to precede price movementThis project is currently an evolving research tool we call MindQuant AI.The idea is that tools for understanding markets probably shouldn’t be static - because narratives and behavior in markets constantly change.So I’m curious how others think about this.If you were building a market intelligence system, what signals would you want it to track?

建立一个系统来跟踪市场叙事和行为信号