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X (Twitter) brand sentiment analysis with Gemini AI & Slack alerts

Saeculum SolutionsSaeculum Solutions
78 views
2/3/2026
LoggingBigQueryData ExtractionGoogle CloudMonitoring
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This workflow is the AI analysis and alerting engine for a complete social media monitoring system. It's designed to work with data scraped from X (formerly Twitter) using a tool like the Apify Tweet Scraper, which logs the data into a Google Sheet. The workflow then automatically analyzes new tweets with Google Gemini and sends tailored alerts to Slack.

How it works

This workflow automates the analysis and reporting part of your social media monitoring:

  • tweet Hunting: It finds tweets for the query entered in the set node and passes the data to the google sheets
  • Fetches New Tweets: It gets all new rows from your Google Sheet that haven't been processed yet (it looks for "Notmarked" in the 'action taken' column).
  • Prepares for AI: It combines the data from all new tweets into a single, clean prompt for the AI to analyze.
  • AI Analysis with Gemini: It sends the compiled data to Google Gemini, asking for a full summary report and a separate, machine-readable JSON list of any urgent items.
  • Splits the Response: The workflow intelligently separates the AI's text summary from the JSON data for urgent alerts.
  • Sends Notifications:
    • The high-level summary is sent to a general Slack channel (e.g., #brand-alerts).
    • Each urgent item is sent as a separate, detailed alert to a high-priority Slack channel (e.g., #urgent).

Set up steps

It should take about 5-10 minutes to get this workflow running.

  1. Prerequisite - Data Source: Ensure you have a Google Sheet being populated with tweet data. For a complete automation, you can set up a new google sheet with the same structure for saving the tweets data and run the Tweet Scraper on a schedule.
  2. Configure Credentials: Make sure you have credentials set up in your n8n instance for Google Sheets, Google Gemini (PaLM) API, and Slack.
  3. Google Sheets Node ("Get row(s) in sheet"):
    • Select your Google Sheet containing the tweet data.
    • Choose the specific sheet name from the dropdown.
    • Ensure your sheet has a column named action taken so the filter works correctly.
  4. Google Gemini Chat Model Node: Select your Google Gemini credential from the dropdown.
  5. Slack Nodes ("Send a message" & "Send a message1"):
    • In the first Slack node, choose the channel for the summary report.
    • In the second Slack node, choose the channel for urgent alerts.
  6. Save and Activate: Once configured, save your workflow and turn it on!

n8n Workflow: X (Twitter) Brand Sentiment Analysis with Gemini AI and Slack Alerts

This n8n workflow automates the process of analyzing sentiment for tweets mentioning a specific brand, using Google Gemini AI, and then sending alerts to Slack for tweets with negative sentiment. It's designed to help you quickly identify and respond to critical feedback or mentions about your brand on X (Twitter).

What it does

This workflow simplifies brand monitoring and sentiment analysis by:

  1. Fetching Brand Mentions: Periodically retrieves recent tweets mentioning a specified brand from a Google Sheet.
  2. Processing Tweets in Batches: Processes the fetched tweets in manageable batches to optimize API calls.
  3. Analyzing Sentiment with Google Gemini: Uses the Google Gemini AI model to determine the sentiment (positive, negative, or neutral) of each tweet.
  4. Filtering Negative Sentiment: Identifies tweets that have been classified with a negative sentiment.
  5. Preparing Slack Alerts: Formats the negative sentiment tweets into a clear and actionable message for Slack.
  6. Sending Slack Alerts: Posts the formatted alerts to a designated Slack channel, ensuring your team is immediately aware of critical brand mentions.
  7. Rate Limiting: Includes a wait step to manage API call rates, preventing rate limit issues with external services.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Google Sheets Credential: An n8n credential configured for Google Sheets to read tweet data.
  • Google Gemini AI Credential: An n8n credential for Google Gemini (or a compatible LLM) to perform sentiment analysis.
  • Slack Credential: An n8n credential configured for Slack to send alerts.
  • Google Sheet: A Google Sheet containing the tweets you wish to analyze. The workflow expects a column named Tweet Text containing the tweet content.
  • X (Twitter) Data: This workflow assumes you have a mechanism (not included in this JSON) to populate the Google Sheet with X (Twitter) brand mentions.

Setup/Usage

  1. Import the Workflow:

    • Download the provided JSON file.
    • In your n8n instance, go to "Workflows" and click "New".
    • Click the three dots menu (...) and select "Import from JSON".
    • Paste the JSON content or upload the file.

  2. Configure Credentials:

    • Google Sheets: Update the "Google Sheets" node with your Google Sheets credential. Ensure the spreadsheet ID and sheet name are correctly configured to point to your tweet data.
    • Google Gemini Chat Model: Update the "Google Gemini Chat Model" node with your Google Gemini credential.
    • Slack: Update the "Slack" node with your Slack credential and specify the target channel for alerts.

  3. Customize AI Prompt (Optional):

    • The "Basic LLM Chain" node contains the prompt for the Google Gemini AI. You might want to adjust this prompt to fine-tune the sentiment analysis for your specific brand or industry.

  4. Activate the Workflow:

    • Once all credentials and configurations are set, activate the workflow.
    • The "Schedule Trigger" node is configured to run every hour, but you can adjust this frequency as needed.

  5. Monitor Slack:

    • Negative sentiment tweets will now be automatically posted to your configured Slack channel.

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