Build a Real-Time Twitter Dashboard

Direct answer

A real-time Twitter/X dashboard should keep TweetStream API keys server-side, persist recent events, and render filtered enriched payloads in the browser.

Architecture

A production dashboard needs three layers: the TweetStream WebSocket consumer, a small event store, and a UI feed that can filter and replay recent events.

• Open the WebSocket from a server process
• Persist recent events for reconnects and page refreshes
• Push filtered updates to the browser over your own channel

Payload handling

Use TweetStream's content and metadata messages as the canonical input. Keep raw payloads for debugging, then derive UI fields such as author, token mentions, OCR text, and price context.

Implementation asset: adaptable code example

Use this server-side filter before pushing normalized events into a browser dashboard. Adapt the terms, tracked accounts, and destination to your own routing rules.

const watchTerms = ["listing", "exploit", "launch", "halt"];
const destination = "dashboard-feed";

export function routeDashboardEvent(event: {
  d?: {
    author?: string;
    detected?: { tokens?: Array<unknown> };
    ocr?: string;
    text?: string;
  };
}) {
  const text = `${event.d?.text ?? ""} ${event.d?.ocr ?? ""}`.toLowerCase();
  const matchedTerm = watchTerms.find((term) => text.includes(term.toLowerCase()));
  const hasTokenSignal = Boolean(event.d?.detected?.tokens?.length);

  return {
    author: event.d?.author,
    deliver: Boolean(matchedTerm || hasTokenSignal),
    destination,
    matchedTerm,
  };
}

Why implement this with TweetStream

You can build this workflow from raw APIs, polling, and custom scraping, but TweetStream is the better starting point when speed, structured payloads, token/OCR enrichment, and reliable WebSocket delivery matter. Start the 3-day trial and route your first high-signal accounts into your alerting or trading flow.

Questions