How to use Rows AI for sentiment analysis

Learn how to use Rows AI for sentiment analysis. Discover step-by-step instructions and tips to effectively analyze sentiments using Rows AI.

Rows AI Template

There's a near-infinite amount of tasks you can solve using Rows AI. Use this template showcase to get started with +10 pre-built examples.

About Rows

Rows is the easiest way to import, transform, and share data in a spreadsheet. It combines a spreadsheet editor, +50 integrations with the tools you use every day, a powerful AI Analyst✨, and a sharing experience to instantly turn any spreadsheet into a web app, a form, or a dashboard.

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Connect the Rows AI integration

To connect the integration, open a new spreadsheet, and search for the Rows AI inside the Data panel.

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Finally, Connect the integration to get started.

Use the Sentiment Analysis action

Once the integration is connected, you can start using OpenAI in Rows to perform sentiment analysis on any piece of text.

Sentiment analysis wizard

Alternatively, you can use the Sentiment analysis function directly in the spreadsheet. Type =SENTIMENT_ANALYSIS to see the autocomplete.

Sentiment Analysis editor

All OpenAI functions need to be configured through mandatory and optional parameters, depending on their purpose. Let's go through them.

Text

The Sentiment Analysis function only requires one parameter, the text. This is simply the text you want to run sentiment analysis on.

You can write the text directly inside the text field in the action wizard, or reference any cell in the table by pointing to it on the editor.

Action w: cell reference

The action will automatically classify the sentiment between: Very positive, Positive, Neutral, Negative or Very Negative.

The remaining parameters are all optional and commonly used for advanced use cases. Learn more about them in the Sentiment analysis function documentation.

Examples

There are several ways to use OpenAI for sentiment analysis:

  • Classify sentiment in social media comments: Determine the overall sentiment on comments on your (or competitors') social media profiles.
  • Rate sentiment from customer feedback: Determine the customer sentiment on product reviews, or feedback survey responses.

Classify sentiment in social media comments or customer feedback

Goal

Analyze comments from social media accounts or any piece of content, and extract the sentiment from the text.

Example:

1=SENTIMENT_ANALYSIS_AI(A2)

Details:

Add the social comment to be analyzed as the first argument (here, cell A2).

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💡 Use our Zapier or Make connector to automatically add a new row in the spreadsheet for a new comment to your social media profiles, customer support emails to your ticketing tool or replies to a feedback form.



Ready to get started?

Try this example and more in our template showcase , or create your first spreadsheet at https://rows.com