Identify reaction post sentiment using AI

Below is a free classifier to identify reaction post sentiment. Just input your text, and our AI will predict the sentiment of your reaction post - in just seconds.

reaction post sentiment identifier

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("reaction-post-sentiment", "your_text_here", credentials)
            

fetch('https://www.nyckel.com/v1/functions/reaction-post-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/reaction-post-sentiment/invoke
            

How this classifier works

To start, input the text that you'd like analyzed. Our AI tool will then predict the sentiment of your reaction post.

This pretrained text model uses a Nyckel-created dataset and has 20 labels, including Angry, Cheerful, Content, Disappointed, Dissatisfied, Enthusiastic, Frustrated, Hopeful, Mixed and Negative.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of your reaction post).

Whether you're just curious or building reaction post sentiment detection into your application, we hope our classifier proves helpful.

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Need to identify reaction post sentiment at scale?

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



  • Social Media Monitoring: Businesses can utilize the 'reaction post sentiment' identifier to monitor customer feedback and sentiment in real-time across various social media platforms. This helps companies to quickly respond to negative sentiments and engage with positive feedback, thereby improving their online reputation.

  • Customer Feedback Analysis: Organizations can automate the analysis of customer feedback collected through reaction posts on surveys or forums. By identifying sentiments, businesses can gain insights into customer satisfaction levels and areas that require improvement.

  • Marketing Campaign Optimization: Marketers can apply this sentiment identifier to gauge how well their campaigns resonate with audiences through user reactions. By analyzing sentiment trends, they can adjust messaging and strategies to enhance campaign effectiveness.

  • Product Development Insights: Companies can leverage sentiment analysis on product-related posts to understand consumer preferences and pain points. This information can guide product development teams in refining existing products or creating new ones that better meet customer needs.

  • Crisis Management: In the event of a PR crisis, organizations can use sentiment analysis to track the shift in public perception over time. By identifying negative sentiments early, they can take proactive measures to mitigate damage and rebuild trust.

  • Competitive Analysis: Businesses can monitor sentiment around competitors’ products or services through social media reaction posts. Analyzing this sentiment can provide insights into competitors' strengths and weaknesses, assisting in strategic decision-making.

  • Influencer Partnership Evaluation: Brands can assess the sentiment of reactions towards influencer posts related to their products. This helps in determining the effectiveness of influencer partnerships and ensuring alignment with brand values and consumer interests.

Want this classifier for your business?

In just minutes you can automate a manual process or validate your proof-of-concept.

Get Access