Identify if a text contains a negative sentiment using AI

Below is a free classifier to identify if a text contains a negative sentiment. Just input your text, and our AI will predict if a text contains a negative sentiment - in just seconds.

if a text contains a negative sentiment identifier

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    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("if-a-text-contains-a-negative-sentiment", "your_text_here", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/if-a-text-contains-a-negative-sentiment/invoke', {
        method: 'POST',
        headers: {
            'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
            'Content-Type': 'application/json',
        },
        body: JSON.stringify(
            {"data": "your_text_here"}
        )
    })
    .then(response => response.json())
    .then(data => console.log(data));
                

    curl -X POST \
        -H "Content-Type: application/json" \
        -H "Authorization: Bearer YOUR_BEARER_TOKEN" \
        -d '{"data": "your_text_here"}' \
        https://www.nyckel.com/v1/functions/if-a-text-contains-a-negative-sentiment/invoke
                

How this classifier works

To start, input the text that you'd like analyzed. Our AI tool will then predict if a text contains a negative sentiment.

This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Positive Sentiment and Negative Sentiment.

We'll also show a confidence score (the higher the number, the more confident the AI model is around if a text contains a negative sentiment).

Whether you're just curious or building if a text contains a negative sentiment detection into your application, we hope our classifier proves helpful.

Recommended Classifiers

Need to identify if a text contains a negative sentiment at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Customer Feedback Analysis: This function can be used to analyze customer feedback across different platforms, such as surveys, reviews, and social media comments. By identifying negative sentiments, businesses can quickly address issues, improve customer satisfaction, and enhance their products or services.

  • Brand Reputation Management: Companies can implement this text classification function to monitor brand mentions and sentiment on social media and news outlets. Identifying negative sentiments in real-time allows businesses to respond promptly, manage crises effectively, and protect their brand reputation.

  • Employee Satisfaction Tracking: Organizations can utilize this tool to analyze employee feedback from internal surveys or forums. By detecting negative sentiments, HR departments can identify areas of concern, take corrective actions, and foster a more positive workplace culture.

  • Product Development Insights: This function can help product teams evaluate customer feedback on existing products or prototypes by detecting negative sentiments. Insights gleaned from this analysis can inform design improvements, feature adjustments, and ultimately lead to a better user experience.

  • Market Research: Marketing teams can leverage this text classification to sift through online reviews, comments, and discussions about competitors and market trends. By pinpointing negative sentiments, they can uncover weaknesses in rival offerings and identify opportunities for differentiation.

  • Customer Support Optimization: Businesses can apply this identifier to prioritize customer support tickets that contain negative sentiment. By triaging these issues, support teams can address urgent problems more effectively, improving resolution times and overall customer satisfaction.

  • Content Moderation: Online platforms can use this function to filter user-generated content for negative sentiments that violate community guidelines. Automated moderation can help maintain a positive environment, reduce toxicity, and improve user experience on forums and social media platforms.

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