Identify letter sentiment
using AI
Below is a free classifier to identify letter sentiment. Just input your text, and our AI will predict the sentiment of the letter it analyzes - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("letter-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/letter-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/letter-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 the letter it analyzes.
This pretrained text model uses a Nyckel-created dataset and has 20 labels, including Affectionate, Cheerful, Critical, Cynical, Disapproving, Encouraging, Grateful, Hopeful, Indifferent and Joyful.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of the letter it analyzes).
Whether you're just curious or building letter sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify letter 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 classify the sentiment of customer feedback letters to quickly identify positive, negative, or neutral sentiments. Businesses can leverage this data to improve products and services based on customer experience.
- Employee Engagement Monitoring: HR departments can utilize the sentiment identifier to analyze letters or emails from employees to gauge overall morale and engagement levels. By understanding sentiment trends, HR can implement necessary changes to enhance workplace satisfaction.
- Brand Reputation Management: Companies can analyze letters sent to and from their customers to track sentiment towards their brand. This proactive approach allows businesses to address potential issues before they escalate, thus maintaining a positive brand image.
- Market Research Insights: By evaluating sentiment in letters related to market trends, businesses can gain insights into consumer preferences and pain points. This analysis can inform product development and marketing strategies based on genuine customer sentiment.
- Legal Document Review: Law firms can use the sentiment identifier to classify the tone of correspondence in legal letters, ensuring that communication aligns with clients' best interests. Understanding the sentiment can help in strategizing responses or adjustments in legal arguments.
- Conflict Resolution in Customer Service: The sentiment analysis can assist customer service teams by identifying emotionally charged letters requiring immediate attention. By prioritizing such cases, companies can enhance customer satisfaction and resolve issues more effectively.
- Social Media Sentiment Tracking: Businesses can extend the function to monitor and analyze letters or communications referencing their brand across various platforms. This will help them to stay ahead of public sentiment and engage with customers effectively during crises or trending discussions.