Identify employee feedback sentiment
using AI
Below is a free classifier to identify employee feedback sentiment. Just input your text, and our AI will predict the sentiment of employee feedback. - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("employee-feedback-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/employee-feedback-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/employee-feedback-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 employee feedback..
This pretrained text model uses a Nyckel-created dataset and has 14 labels, including Complaint, Constructive, Critical, Discouraging, Dissatisfied, Encouraging, Negative, Neutral, Positive and Praise.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of employee feedback.).
Whether you're just curious or building employee feedback sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify employee feedback sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Employee Satisfaction Monitoring: This use case involves utilizing the sentiment identification function to continuously assess employee feedback provided through surveys and questionnaires. By analyzing the sentiment behind these responses, HR can quickly identify areas of concern that may require intervention to boost overall job satisfaction.
- Performance Review Insights: The function can be applied to collect and analyze employee feedback at the time of performance reviews. By gauging the sentiment in comments and feedback, managers can gain deeper insights into employee perceptions of their roles and the effectiveness of leadership, leading to more constructive performance evaluations.
- Training and Development Needs Assessment: Organizations can use sentiment analysis on employee feedback regarding training programs and development initiatives. This analysis can identify specific areas where employees feel unsupported or undertrained, allowing the company to adjust its offerings to better meet workforce needs.
- Change Management Evaluation: During organizational changes, such as restructuring or mergers, sentiment analysis can help gauge employee reactions to the changes. By analyzing feedback sentiment, leadership can better understand employee concerns and adapt their change management strategies accordingly.
- Employee Engagement Programs: Companies can leverage the sentiment identification function to evaluate the effectiveness of employee engagement programs. By analyzing sentiment from feedback collected after initiatives, organizations can identify what resonates with employees and adjust their strategies to foster a more engaged workforce.
- Exit Interview Analysis: When employees leave the organization, sentiment analysis can be applied to their feedback during exit interviews. This allows HR to identify common themes or issues that lead to turnover, enabling the organization to address these factors and improve retention strategies.
- Conflict Resolution Improvement: The sentiment function can assist in monitoring internal communication to identify signs of conflict or dissatisfaction among employees. By proactively identifying negative sentiment trends, organizations can intervene before issues escalate, fostering a more cooperative workplace environment.