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Google Cloud Natural Language

5 Ergebnisse — ausschließlich quellenverknüpfte n8n-Referenzen

googlecloudnaturallanguagenotiontrello
free

Route Feedback by Sentiment Using Typeform, GCP Natural Language, Notion & Trello

Feedback Sentiment Workflow (Typeform → GCP → Notion/Slack/Trello) This template ingests feedback from Typeform, runs Google Cloud Natural Language sentiment analysis, routes based on sentiment, and then creates a Notion database page and posts a Slack notification for positive items, or creates a Trello card for negative items. The flow is designed for quick setup and safe sharing using placeholders for IDs and credentials. How it Works Typeform Trigger Captures each new submission and exposes answers like Name and the long-text Feedback field. Google Cloud Natural Language Analyzes the feedback text and returns a sentiment score in: documentSentiment.score Check Sentiment Score (IF) True branch: Score > 0 → Positive False branch: Score ≤ 0 → Non-positive Add Feedback to Notion (True branch) Creates a new page in a Notion database with mapped properties. Notify Slack (after Notion) Posts the feedback, author, and score to a Slack channel for visibility. Create Trello Card (False branch) Logs non-positive items to a Trello list for follow-up. Required Accounts Google Cloud Natural Language API** enabled (OAuth2 or service credentials). Notion integration** with database access t

von Yatharth Chauhan
googlecloudnaturallanguagestrapixformerlytwitter
free

Automate testimonials in Strapi with n8n

This is the workflow powering the n8n demo shown at StrapiConf 2022. The workflow searches matching Tweets every 30 minutes using the Interval node and listens to Form submissions using the Webhook node. Sentiment analysis is handled by Google using the Google Cloud Natural Language node before the result is stored in Strapi using the Strapi node. (These were originally two separate workflows that have been combined into one to simplify sharing.)

von Tom
googlecloudnaturallanguagenotiontrello
free

Add positive feedback messages to a table in Notion

This workflow allows you to add positive feedback messages to a table in Notion. Prerequisites Create a Typeform that contains Long Text filed question type to accepts feedback from users. Get your Typeform credentials by following the steps mentioned in the documentation. Follow the steps mentioned in the documentation to create credentials for Google Cloud Natural Language. Create a page on Notion similar to this page. Create credentials for the Notion node by following the steps in the documentation. Follow the steps mentioned in the documentation to create credentials for Slack. Follow the steps mentioned in the documentation to create credentials for Trello. Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form. Google Cloud Natural Language node: This node analyses the sentiment of the response the user has provided and gives a score. IF node: The IF node uses the score provided by the Google Cloud Natural Language node and checks if the score is positive (larger than 0). If the score is positive we get the result as True, otherwise F

von Harshil Agrawal
googlecloudnaturallanguagemongodbpostgres
free

ETL pipeline for text processing

This workflow allows you to collect tweets, store them in MongoDB, analyse their sentiment, insert them into a Postgres database, and post positive tweets in a Slack channel. Cron node: Schedule the workflow to run every day Twitter node: Collect tweets MongoDB node: Insert the collected tweets in MongoDB Google Cloud Natural Language node: Analyse the sentiment of the collected tweets Set node: Extract the sentiment score and magnitude Postgres node: Insert the tweets and their sentiment score and magnitude in a Posgres database IF node: Filter tweets with positive and negative sentiment scores Slack node: Post tweets with a positive sentiment score in a Slack channel NoOp node: Ignore tweets with a negative sentiment score

von Lorena
googlecloudnaturallanguagemattermost
free

Analyze feedback and send a message on Mattermost

This workflow analyzes the sentiments of the feedback provided by users and sends them to a Mattermost channel. Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form. Google Cloud Natural Language node: This node analyses the sentiment of the response the user has provided and gives a score. IF node: The IF node uses the score provided by the Google Cloud Natural Language node and checks if the score is negative (smaller than 0). If the score is negative we get the result as True, otherwise False. Mattermost node: If the score is negative, the IF node returns true and the true branch of the IF node is executed. We connect the Mattermost node with the true branch of the IF node. Whenever the score of the sentiment analysis is negative, the node gets executed and a message is posted on a channel in Mattermost. NoOp: This node here is optional, as the absence of this node won't make a difference to the functioning of the workflow. This workflow can be used by Product Managers to analyze the feedback of the product. The workflow can also be use

von Harshil Agrawal