Identify instant message sentiment
using AI
Below is a free classifier to identify instant message sentiment. Just input your text, and our AI will predict the sentiment of your instant messages. - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("instant-message-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/instant-message-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/instant-message-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 instant messages..
This pretrained text model uses a Nyckel-created dataset and has 12 labels, including Critical, Disappointed, Enthusiastic, Mixed Sentiment, Negative, Neutral, Positive, Slightly Negative, Slightly Positive and Supportive.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of your instant messages.).
Whether you're just curious or building instant message sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify instant message sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Support Optimization: This use case involves organizations utilizing the instant message sentiment identifier to assess customer queries in real time. By analyzing the sentiment of customer messages, support teams can prioritize urgent or negative interactions and respond more effectively, enhancing overall customer satisfaction.
- Brand Reputation Management: Companies can leverage sentiment analysis to monitor customer opinions on social media and instant messaging platforms. Early detection of negative sentiments allows organizations to address potential PR issues swiftly, helping to maintain a positive brand image.
- Market Research Insights: Businesses can apply sentiment classification to analyze customer feedback within instant messaging channels. By identifying trends in customer sentiment regarding products or services, companies can make informed decisions on product improvements or new offerings.
- Employee Engagement Monitoring: HR departments can utilize sentiment analysis to evaluate the emotional tone of internal communications via instant messaging platforms. This insight can help identify areas of concern within teams, improve employee morale, and foster a more positive work environment.
- Personalization of Marketing Campaigns: Marketers can use the sentiment identifier to gauge customer sentiments interacting with automated messaging. With this data, campaigns can be tailored based on customer feelings, increasing engagement and conversion rates.
- Chatbot Performance Enhancement: Businesses deploying chatbots can integrate sentiment analysis to measure the effectiveness of conversations. By understanding customer sentiments during interactions, companies can fine-tune chatbot responses and improve customer experience.
- Conflict Resolution: Organizations can employ the sentiment identifier during team communications to identify potential conflicts early on. By quickly recognizing negative sentiments, management can intervene proactively and facilitate constructive dialogues to prevent escalation.