Identify user profile sentiment
using AI
Below is a free classifier to identify user profile sentiment. Just input your text, and our AI will predict the user's sentiment about a specific topic. - 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("user-profile-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/user-profile-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/user-profile-sentiment/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the user's sentiment about a specific topic..
This pretrained text model uses a Nyckel-created dataset and has 20 labels, including Apprehensive, Confident, Critical, Disappointed, Dissatisfied, Doubtful, Enthusiastic, Hopeful, Mixed and Negative.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the user's sentiment about a specific topic.).
Whether you're just curious or building user profile sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify user profile sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Service Improvement: Utilize the user profile sentiment identifier to assess customer interactions and feedback. By analyzing the sentiment of users, businesses can identify patterns and areas that need improvement, ultimately enhancing customer service strategies and increasing satisfaction.
- Targeted Marketing Campaigns: Leverage sentiment analysis to tailor marketing efforts based on user profiles. By understanding customer sentiment, businesses can design more personalized and relevant marketing campaigns, leading to higher engagement rates and increased sales.
- Product Development Insights: Use the identifier to gather insights on user sentiments about existing products. This information can guide product teams in making informed decisions about enhancements, feature requests, and new product ideas based on actual user preferences and feelings.
- Brand Reputation Management: Monitor user sentiment connected to brand mentions across social media and online platforms. By identifying negative sentiments early, businesses can proactively address issues and manage their online reputation effectively.
- Employee Engagement Analysis: Implement the sentiment identifier to assess employee feedback through surveys and internal communications. Understanding employee sentiments helps HR teams to identify morale trends and address any concerns before they escalate.
- Churn Prediction and Prevention: Analyze sentiment data from user interactions to identify at-risk customers showing negative sentiments. By targeting these users with personalized outreach or offers, businesses can mitigate churn and strengthen customer retention efforts.
- Community Management Optimization: Apply sentiment classification to analyze feedback within community forums or user groups. By identifying overall sentiment trends, community managers can enhance user engagement strategies and foster a more positive environment for discussions.