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Find, scrape & analyze Twitter posts by name with Bright Data & Gemini

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2/3/2026
Google SheetsAI SummarizationOpenAIAutomationData Enrichment
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This n8n workflow template automates the process of collecting and analyzing Twitter (X) posts for any public profile, then generates a clean, AI-powered summary including key metrics, interests, and activity trends.

🚀 What It Does

  • Accepts a user's full name and date range through a public form.
  • Automatically finds the person’s X (formerly Twitter) profile using a Google search.
  • Uses Bright Data to retrieve full post data from the X.com profile.
  • Extracts key post metrics like views, likes, reposts, hashtags, and mentions.
  • Uses Google Gemini (PaLM) to generate a personalized summary: tone, themes, popularity, and sentiments.
  • Stores both raw data and the AI summary into a connected Google Sheet for further review or team collaboration.

🛠️ Step-by-Step Setup

  1. Deploy the public form to collect full name and date range.
  2. Build a Google search query using the name to find their X profile.
  3. Scrape the search results via Bright Data (Web Unlocker zone).
  4. Parse the page content using the HTML node.
  5. Use Gemini AI to extract the correct X profile URL.
  6. Pull full post data via Bright Data dataset snapshot API.
  7. Transform post data into clean structured fields: date_posted, description, hashtags, likes, views, quoted_post.date_posted, quoted_post.description, replies, reposts, quotes, and tagged_users.profile_name.
  8. Analyze all posts using Google Gemini for interest detection and persona generation.
  9. Save results to a Google Sheet: structured post data + AI-written summary.
  10. Show success or fallback messages depending on profile detection or scraping status.

🧠 How It Works: Workflow Overview

  • Trigger: When user submits form
  • Search & Match: Google search → HTML parse → Gemini filters matching X profile
  • Data Gathering: Bright Data → Poll for snapshot completion → Fetch post data
  • Transformation: Extract and restructure key fields via Code node
  • AI Summary: Use Gemini to analyze tone, interests, and trends
  • Export: Save results to Google Sheet
  • Fallback: Display custom error message if no X profile found

📨 Final Output

  • A record in your Google Sheet with:
    • Clean post-level data
    • Profile-level engagement summary
    • An AI-written overview including tone, common topics, and post popularity

🔐 Credentials Used

  • Bright Data account (for search & post scraping)
  • Google Gemini (PaLM) or Gemini Flash via - OpenAI/Google Vertex API
  • Google Sheets (OAuth2) account (for result storage)

⚠️Community Node Dependency This workflow uses a custom community node: n8n-nodes-brightdata Install it via UI (Settings → Community Nodes → Install).

Find, Scrape, and Analyze Twitter Posts by Name with Bright Data and Gemini

This n8n workflow automates the process of finding, scraping, and analyzing Twitter posts related to a specific name using Bright Data and Google Gemini. It allows users to input a name via an n8n form, then uses Bright Data to scrape Twitter for relevant posts. These posts are then analyzed by Google Gemini for sentiment and key information, and the results are stored in a Google Sheet.

What it does

  1. Triggers on Form Submission: The workflow starts when a user submits a name through an n8n form.
  2. Sets Search Query: It takes the submitted name and prepares it as a search query for Twitter.
  3. Scrapes Twitter with Bright Data: It uses a Bright Data collector to scrape Twitter for posts containing the specified name.
  4. Extracts HTML Content: It processes the raw HTML output from Bright Data to extract relevant text content from the tweets.
  5. Analyzes Posts with Google Gemini: Each extracted tweet is sent to Google Gemini for analysis, determining sentiment and other key insights.
  6. Parses Gemini Output: The structured output from Google Gemini is parsed to extract the analyzed data.
  7. Conditionally Stores Data: It checks if the Gemini analysis was successful.
    • If successful: The analyzed data (including sentiment, extracted information, and the original tweet) is appended to a Google Sheet.
    • If unsuccessful: The original tweet and an error message are appended to a separate Google Sheet, indicating that analysis failed.
  8. Introduces Delays: Strategic Wait nodes are used to manage API rate limits and ensure smooth operation, especially when dealing with external services like Bright Data and Gemini.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance.
  • Bright Data Account: Credentials for a Bright Data account to use their Twitter scraping collectors.
  • Google Gemini API Key: An API key for Google Gemini (or a compatible Google AI Studio API key) for text analysis.
  • Google Sheets Account: Access to a Google Sheets document where the results will be stored. You will need to configure the specific spreadsheet ID and sheet names within the Google Sheets nodes.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Bright Data: Set up your Bright Data credentials in the "Bright Data Collector" node.
    • Google Gemini: Configure your Google Gemini API key in the "Google Gemini Chat Model" node.
    • Google Sheets: Set up your Google Sheets credentials. For the "Google Sheets" nodes, you will need to specify the Spreadsheet ID and the Sheet Name where the analyzed data and error logs should be stored respectively.
  3. Activate the Workflow: Once all credentials and configurations are set, activate the workflow.
  4. Submit a Name: Access the URL provided by the "On form submission" trigger node and submit a name to initiate the workflow. The workflow will then proceed to scrape Twitter, analyze posts, and update your Google Sheet.

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