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Automate Twitter Sentiment Analysis with OpenAI, Google Sheets, and Slack Alerts
https://n8nworkflows.xyz/workflows/automate-twitter-sentiment-analysis-with-openai--google-sheets--and-slack-alerts-6119
# Automate Twitter Sentiment Analysis with OpenAI, Google Sheets, and Slack Alerts
### 1. Workflow Overview
This workflow automates Twitter sentiment monitoring using Apify, OpenAI, Google Sheets, and Slack. It fetches recent tweets containing a specific hashtag or keyword, analyzes their sentiment with AI models, generates friendly replies for positive sentiments, logs all results in a Google Sheet, and sends Slack alerts for negative tweets. The logical flow is divided into the following blocks:
- **1.1 Trigger and Data Collection:** Periodically trigger the workflow and fetch latest tweets via the Apify API.
- **1.2 Data Preparation and Looping:** Prepare tweet data for processing and iterate over each tweet individually.
- **1.3 Sentiment Analysis:** Use OpenAI-powered AI agents to classify tweet sentiment into Positive, Neutral, or Negative.
- **1.4 Conditional Actions:** Depending on sentiment, generate replies for positive tweets, notify Slack for negative ones, and always log results.
- **1.5 Data Logging:** Append or update processed tweet data and analysis results in Google Sheets for record-keeping.
---
### 2. Block-by-Block Analysis
#### 1.1 Trigger and Data Collection
- **Overview:** This block triggers the workflow every 6 hours to fetch the latest tweets matching a specified query using the Apify API.
- **Nodes Involved:** Schedule Trigger, Request for Twitter Post via Apify, Get Requested Post from Apify
**Node Details:**
- **Schedule Trigger**
- Type: Schedule Trigger
- Role: Initiates the workflow automatically every 6 hours.
- Configuration: Interval set to 6 hours.
- Inputs: None
- Outputs: Connects to "Request for Twitter Post via Apify"
- Failures: None typical, but n8n server downtime would prevent triggering.
- **Request for Twitter Post via Apify**
- Type: HTTP Request
- Role: Posts a request to Apify's Twitter scraper API to fetch the latest 5 tweets with the query "LaraconIn" in English.
- Configuration:
- Method: POST
- URL: Apify API endpoint for scraper actor execution
- Headers: Content-Type application/json
- Body (JSON): Query "LaraconIn", resultsCount 5, searchType latest, lang en
- API Token: Must be replaced with a valid Apify token (`api_key`)
- Inputs: Trigger from Schedule Trigger
- Outputs: Connects to "Get Requested Post from Apify"
- Failures: Network issues, invalid API token, or API rate limits.
- **Get Requested Post from Apify**
- Type: HTTP Request
- Role: Retrieves the latest dataset items (tweets) from the last Apify run.
- Configuration:
- Method: GET
- URL: Apify API endpoint for last run dataset items with token
- Inputs: Output from "Request for Twitter Post via Apify"
- Outputs: Connects to "Set Field for Loop"
- Failures: Network issues, dataset not available, invalid token.
---
#### 1.2 Data Preparation and Looping
- **Overview:** Prepares and formats each tweet's essential data fields, then loops over individual tweets for sequential processing.
- **Nodes Involved:** Set Field for Loop, Loop Over Items, Get Post Data, If Duplicate (inactive)
**Node Details:**
- **Set Field for Loop**
- Type: Set
- Role: Extracts and renames tweet data fields (`postId` → `id`, `postUrl` → `tweet_url`, `postText` → `tweet_text`) for easier reference downstream.
- Configuration: Assigns `id`, `tweet_url`, `tweet_text` from incoming JSON.
- Inputs: Output from "Get Requested Post from Apify"
- Outputs: Connects to "Loop Over Items"
- Failures: Expression failures if incoming data missing expected fields.
- **Loop Over Items**
- Type: Split In Batches
- Role: Iterates over tweets one at a time to allow sequential processing and API calls.
- Configuration: Default batch size (1), no special options.
- Inputs: Output from "Set Field for Loop"
- Outputs: Two outputs:
- First: To "Get Post Data" (to check duplicates)
- Second: Empty (unused)
- Failures: If input is empty, no iteration occurs.
- **Get Post Data**
- Type: Google Sheets
- Role: Queries the Google Sheet to check if the tweet ID already exists (to avoid duplicates).
- Configuration:
- Document ID and Sheet Name fixed to a specific Google Sheet and tab.
- Filter by the tweet ID column matching current tweet ID.
- Inputs: Output from "Loop Over Items"
- Outputs: Connects to inactive "If Duplicate"
- Failures: Google Sheets auth errors, rate limits, or incorrect document/sheet IDs.
- **If Duplicate**
- Type: If Node
- Role: Intended to check if the tweet already exists in the sheet and branch accordingly.
- Configuration: Checks if the Google Sheets query returned an existing ID.
- Inputs: Output from "Get Post Data"
- Outputs: Two branches (true/false) but node is inactive.
- Note: This node is currently inactive, so duplicate checking is effectively bypassed.
---
#### 1.3 Sentiment Analysis
- **Overview:** Analyzes tweet sentiment using AI models and generates a short reply for positive tweets.
- **Nodes Involved:** Sentiment Analyst, Structured Output Parser, Switch According Analyst, OpenAI, OpenAI Chat Model
**Node Details:**
- **Sentiment Analyst**
- Type: Langchain Agent Node (AI agent)
- Role: Classifies the sentiment of the tweet text into one word: Positive, Neutral, or Negative.
- Configuration:
- Input Text: Gets `tweet_text` from current loop item.
- System Message: Defines the assistant's role to classify sentiment strictly into one word.
- Output Parser: Enabled for structured output.
- Inputs: Output from "Loop Over Items" (via "OpenAI Chat Model")
- Outputs: Connects to "Switch According Analyst"
- Failures: AI service downtime, malformed input, or parsing errors.
- **Structured Output Parser**
- Type: Langchain Output Parser
- Role: Parses AI output into structured JSON, expecting a "category" field.
- Configuration: JSON schema example with category string.
- Inputs: AI response
- Outputs: Connects back to "Sentiment Analyst" for parsing.
- Failures: Output not matching schema leads to parsing errors.
- **OpenAI Chat Model**
- Type: Langchain Chat Model Node
- Role: Provides the AI language model used by Sentiment Analyst for sentiment classification.
- Configuration:
- Model: GPT-4O-mini
- Inputs: None direct, triggered internally.
- Outputs: Connects to Sentiment Analyst's AI Language Model input.
- Failures: OpenAI API failures, quota limits.
- **Switch According Analyst**
- Type: Switch
- Role: Routes workflow based on sentiment category: Positive → generate reply, Negative → send Slack alert, Neutral → just log.
- Configuration: Conditions check the `output.category` field for "Positive", "Negative", or "Neutral".
- Inputs: Output from "Sentiment Analyst"
- Outputs:
- Positive: Connects to "OpenAI" node to generate reply
- Negative: Connects to Slack notification node
- Neutral: Connects directly to logging (Google Sheets)
- Failures: Misclassification, typos in category values (note "Nagative" typo in rules, but mapped correctly).
- **OpenAI**
- Type: Langchain OpenAI Node
- Role: Generates a friendly, thoughtful reply from a user's perspective for positive tweets.
- Configuration:
- Model: GPT-4O-mini
- System message instructs to write a friendly, intelligent reply under 160 characters, no emojis, addressing the poster directly.
- Uses tweet text from Set Field for Loop.
- Inputs: From "Switch According Analyst" positive branch
- Outputs: Connects to "Add Post Data"
- Failures: OpenAI API errors, malformed input.
---
#### 1.4 Conditional Actions
- **Overview:** Depending on sentiment, the workflow sends Slack alerts for negative tweets and logs all processed tweets.
- **Nodes Involved:** Send negative post message on slack
**Node Details:**
- **Send negative post message on slack**
- Type: Slack Node
- Role: Sends a Slack message alerting about a negative tweet with its URL.
- Configuration:
- Channel: Fixed channel ID `C090F70N52M` (e.g., "website-uptime" channel)
- Message: Includes tweet URL from "Check Duplicate" (note: node "Check Duplicate" not present, likely a labeling inconsistency; actually receives from "Switch According Analyst")
- Authentication: Uses OAuth2 Slack credentials.
- Inputs: From "Switch According Analyst" negative branch
- Outputs: Connects to "Add Post Data"
- Failures: Slack API rate limits, auth token expiration.
---
#### 1.5 Data Logging
- **Overview:** Appends or updates the Google Sheet with tweet ID, URL, text, sentiment, and post reply (if any).
- **Nodes Involved:** Add Post Data
**Node Details:**
- **Add Post Data**
- Type: Google Sheets Node
- Role: Writes or updates the tweet data and sentiment analysis results into the Google Sheet.
- Configuration:
- Document and Sheet same as "Get Post Data"
- Columns mapped: ID, TweetUrl, TweetText, Sentiment, Post Reply
- Operation: Append or Update based on matching ID
- Inputs: From "OpenAI", "Send negative post message on slack", and "Switch According Analyst" neutral branch
- Outputs: Connects back to "Loop Over Items" for processing next tweet
- Failures: Google Sheets API errors, malformed data, permission issues.
---
### 3. Summary Table
| Node Name | Node Type | Functional Role | Input Node(s) | Output Node(s) | Sticky Note |
|---------------------------------|-----------------------------|---------------------------------------------------|--------------------------------|---------------------------------------|--------------------------------------------------------------------------------------------------|
| Schedule Trigger | Schedule Trigger | Triggers workflow every 6 hours | None | Request for Twitter Post via Apify | |
| Request for Twitter Post via Apify | HTTP Request | Fetches latest tweets from Apify | Schedule Trigger | Get Requested Post from Apify | |
| Get Requested Post from Apify | HTTP Request | Retrieves tweet data from Apify dataset | Request for Twitter Post via Apify | Set Field for Loop | |
| Set Field for Loop | Set | Formats tweet fields for processing | Get Requested Post from Apify | Loop Over Items | |
| Loop Over Items | Split In Batches | Iterates over tweets one by one | Set Field for Loop | Get Post Data (primary), empty output | |
| Get Post Data | Google Sheets | Checks for duplicates in Google Sheets | Loop Over Items | If Duplicate | |
| If Duplicate | If | Intended to branch based on duplicates (inactive) | Get Post Data | Loop Over Items (true), Sentiment Analyst (false) | |
| Sentiment Analyst | Langchain Agent Node | Classifies tweet sentiment | Loop Over Items (via OpenAI Chat Model) | Switch According Analyst | |
| Structured Output Parser | Langchain Output Parser | Parses AI output into structured JSON | Sentiment Analyst | Sentiment Analyst (parser output) | |
| OpenAI Chat Model | Langchain Chat Model | Provides AI model for sentiment classification | None | Sentiment Analyst (AI model input) | |
| Switch According Analyst | Switch | Routes workflow based on sentiment category | Sentiment Analyst | OpenAI (Positive), Slack (Negative), Add Post Data (Neutral) | |
| OpenAI | Langchain OpenAI Node | Generates friendly replies for positive tweets | Switch According Analyst | Add Post Data | |
| Send negative post message on slack | Slack Node | Sends Slack alert for negative tweets | Switch According Analyst | Add Post Data | |
| Add Post Data | Google Sheets | Logs or updates tweet data and analysis results | OpenAI, Slack, Switch According Analyst | Loop Over Items | |
| Sticky Note | Sticky Note | Provides workflow summary and usage notes | None | None | [Sample Output Sheet and Workflow Summary](https://docs.google.com/spreadsheets/d/1sOxYQtX-O6p35FCNSRsovKEHL4w4GsfF-ylMVcwpb_E/edit?usp=sharing) |
---
### 4. Reproducing the Workflow from Scratch
1. **Create a Schedule Trigger node**
- Set the trigger interval to every 6 hours.
- This will start the workflow automatically.
2. **Create an HTTP Request node ("Request for Twitter Post via Apify")**
- Method: POST
- URL: `https://api.apify.com/v2/acts/scraper_one~x-posts-search/run-sync?token=YOUR_API_TOKEN`
- Headers: Add `Content-Type: application/json`
- Body Type: JSON
- Body:
```json
{
"query": "LaraconIn",
"resultsCount": 5,
"searchType": "latest",
"lang": "en"
}
```
- Connect Schedule Trigger output to this node.
3. **Create a second HTTP Request node ("Get Requested Post from Apify")**
- Method: GET
- URL: `https://api.apify.com/v2/acts/scraper_one~x-posts-search/runs/last/dataset/items?token=YOUR_API_TOKEN`
- Connect output of previous HTTP Request node to this node.
4. **Create a Set node ("Set Field for Loop")**
- Add three fields with expressions:
- `id` = `{{$json.postId}}`
- `tweet_url` = `{{$json.postUrl}}`
- `tweet_text` = `{{$json.postText}}`
- Connect output of "Get Requested Post from Apify" to this node.
5. **Create a Split In Batches node ("Loop Over Items")**
- Default batch size 1.
- Connect output of "Set Field for Loop" to this node.
6. **Create a Google Sheets node ("Get Post Data")**
- Set operation to read rows filtered by the `ID` column matching `{{$json.id}}`.
- Configure Google Sheets credentials.
- Use the specific document ID and sheet name for Twitter data.
- Connect primary output of "Loop Over Items" to this node.
7. **(Optional) Create an If node ("If Duplicate")**
- Condition: Check if the `ID` field exists in data from Google Sheets.
- Connect "Get Post Data" output here.
- (Note: This node is inactive in original workflow.)
8. **Create Langchain Chat Model node ("OpenAI Chat Model")**
- Model: GPT-4O-mini
- Configure OpenAI API credentials.
- No inputs; prepare for use by Sentiment Analyst.
9. **Create Langchain Agent node ("Sentiment Analyst")**
- Text input: `{{$json.tweet_text}}` from current loop item.
- System Message: "You are a helpful AI assistant.Perfectly analyze the sentiment of this tweet_text and tell me in one word it is Positive, Neutral, or Negative."
- Enable Structured Output Parser.
- Connect "Loop Over Items" output to this node.
- Link "OpenAI Chat Model" as AI language model input.
10. **Create Langchain Output Parser node ("Structured Output Parser")**
- JSON Schema example: `{"category": "neutral"}`
- Connect AI output from "Sentiment Analyst" to this parser node.
11. **Create a Switch node ("Switch According Analyst")**
- Add rules for `{{$json.output.category}}` equal to "Positive", "Negative", or "Neutral".
- Connect output of "Sentiment Analyst" to this node.
12. **Create Langchain OpenAI node ("OpenAI")**
- Model: GPT-4O-mini
- System message instructs to write a positive reply:
- Friendly, intelligent, under 160 characters, no emojis, address original poster.
- Message content: `{{$json.tweet_text}}` from "Set Field for Loop"
- Connect "Switch According Analyst" positive branch to this node.
13. **Create Slack node ("Send negative post message on slack")**
- Use Slack OAuth2 credentials.
- Channel: Use appropriate Slack channel ID (e.g., `C090F70N52M`).
- Message: "Received a Negative retweet on {{$json.TweetUrl}}. Consider if a response or clarification is needed."
- Connect "Switch According Analyst" negative branch to this node.
14. **Create Google Sheets node ("Add Post Data")**
- Operation: Append or Update
- Match by `ID`
- Columns:
- ID: `{{$json.id}}`
- TweetUrl: `{{$json.tweet_url}}`
- TweetText: `{{$json.tweet_text}}`
- Sentiment: `{{$json.output.category}}` from Switch node
- Post Reply: `{{$json.message.content}}` from OpenAI node (if applicable)
- Connect outputs of:
- "OpenAI"
- "Send negative post message on slack"
- "Switch According Analyst" neutral branch
to this node.
15. **Connect "Add Post Data" output back to "Loop Over Items" to process next tweet.**
---
### 5. General Notes & Resources
| Note Content | Context or Link |
|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------|
| Sample Output Sheet: https://docs.google.com/spreadsheets/d/1sOxYQtX-O6p35FCNSRsovKEHL4w4GsfF-ylMVcwpb_E/edit?usp=sharing | Google Sheet used for storing tweets and sentiment results |
| This workflow uses Apify's Twitter Scraper API to fetch trending Twitter content programmatically. Replace `YOUR_API_TOKEN` with your actual Apify API token. | https://apify.com/ |
| The OpenAI GPT-4O-mini model is used for both sentiment classification and reply generation, ensuring cohesive AI interactions. | Requires OpenAI API credentials |
| Slack channel ID and Google Sheets document IDs are hardcoded and need to be replaced or configured per user environment. | Slack OAuth2 and Google Sheets OAuth2 credentials required |
| Duplicate checking is implemented but currently disabled (If Duplicate node inactive). This may cause repeated processing of the same tweets. | Consider enabling this node for production use |
| Slack alerts are sent only for negative sentiment tweets to encourage manual review or response. Positive tweets get AI-generated replies, and neutral tweets are logged without further action. | |
---
**Disclaimer:** The provided text is derived exclusively from an n8n automated workflow. All data processed is legal and public, and the workflow complies with content policies.