Identify experience sharing sentiment
using AI
Below is a free classifier to identify experience sharing sentiment. Just input your text, and our AI will predict the sentiment of shared experiences - 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("experience-sharing-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/experience-sharing-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/experience-sharing-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 shared experiences.
This pretrained text model uses a Nyckel-created dataset and has 20 labels, including Appreciative, Constructive, Critical, Cynical, Destructive, Disappointed, Enthusiastic, Hopeful, Indifferent and Mixed.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of shared experiences).
Whether you're just curious or building experience sharing sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify experience sharing sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Experience Insights: This function can analyze shared experiences from customers to identify overall sentiment regarding a product or service. By classifying sentiments as positive, negative, or neutral, businesses can gain insights into areas of improvement and customer satisfaction.
- Social Media Monitoring: Companies can utilize this sentiment identifier to monitor customer experiences shared on social media platforms. By classifying the sentiment of these posts, businesses can respond promptly to negative feedback and capitalize on positive experiences to enhance their brand image.
- Product Development Feedback: The sentiment analysis can be applied to evaluate user-generated content related to new product features. By identifying sentiments related to specific aspects of the product, companies can prioritize refinements that align with customer expectations and preferences.
- Hospitality and Service Enhancements: In the hospitality sector, this function can assess guest reviews and testimonials. Classifying the sentiment helps identify strengths and weaknesses in service delivery, enabling management to tailor training and operational changes for improved customer experiences.
- Brand Reputation Management: This sentiment identifier can be used to gauge public perception of a brand based on shared experiences across various platforms. Businesses can monitor shifts in sentiment over time, allowing them to proactively address potential reputation risks.
- Market Research and Competitive Analysis: Organizations can leverage sentiment analysis to understand competitors’ customer experiences shared publicly. By analyzing competitive sentiment, businesses can identify market trends and areas where they can differentiate themselves.
- Community Engagement and Feedback: Nonprofit organizations can utilize this function to assess community feedback and sentiment on their programs and initiatives. Understanding the sentiments of participants can help organizations enhance engagement strategies and build better relationships with their stakeholders.