Please note: This is a user-restricted feature. Only admin users are able to view sentiment data by default.
Weekly10's Natural Language Processing (NLP) engine leverages artificial intelligence and machine learning technology to provide sentiment analysis. Sentiment analysis allows admins to analyse the results of comment-based responses in check-ins.
This article covers:
What is sentiment?
Sentiment is a measure of how positive or negative someone is when they provide feedback. It has been a leading tool for analysising feedback in the world of marketing for a number of years.
With significant advancements in Artificial Intelligence (AI) and Machine Learning technology over
the past decade - sentiment analysis is now an accurate way to understand the mood of the people in your company.
Weekly10 provides an anonymous, aggregated view of sentiment across your organisation and
allows you to group and filter down to department and team levels. This provides week-by-week insights on how your people really feel based on the feedback in their Weekly10 check-in.
In Weekly10 we provide this sentiment as a measure between 0 and 1. Typically a score below 0.3 is on average considered negative and above 0.7 very positive. Between 0.3 and 0.7 we would term the level of sentiment to be neutral or mixed.
For more information on sentiment
How do I view sentiment data?
Please note: Currently sentiment is only available to view in the web platform. It will be coming to Microsoft Teams in the near future.
- Head to the ‘Organisation’ tab.
- An overview of sentiment is shown in the first data widget on this dashboard (top-left).
- You can also use this widget to view check-in submission data (use the second tab option, labeled 'Check-ins'.
- To view more in-depth sentiment data, select ‘View details’ below the sentiment overview chart.
- Here you can dissect your sentiment data by time period, team, department, or even location if you have multiple.
- Below the chart view, you will also find the raw data (for the selected period/filters). You can export this to CSV for use in Excel or similar if required.