Page History

The Natural Language Analysis report for Teams utilizes leverages advanced AI features like such as natural language processing (NLP) to analyze Teams content, detect content within Microsoft Teams.

It detects key phrases and themes, understand understands multilingual conversations, and analyze analyzes sentiment trends.   These capabilities enhance understanding, promote collaboration, help gauge satisfaction and ensure decisions are well-informed and support data-driven decision-making.

Teams |  Natural Language Analysis

Key Phrases in Messages

The word cloud contains the key phrases detected in messages, which reflects the most discussed topics in Teams. The larger a word is, the more often it is used.

The bar chart displays the top key phrases detected in messages ranked by the number of messages containing the listed phrase and their corresponding positive, neutral or negative sentiment.

Languages Used in Messages

This chart includes a breakdown of messages in each language.

Messages Sentiment Ratio

This chart includes a breakdown of messages in each sentiment.

...

This line graph indicates trends in the messages sentiment over time.

Top Threads

This table visual displays the top threads ranked by the number of contributors. It includes the following columns:

• Root Message - The first message of the listed thread.
• Responders - The number of users who posted at least one reply in the listed thread during the selected date range.
• Replies - The number of replies in the listed thread during the selected date range.
• Likes - The number of likes for the listed thread during the selected date range.
• Positive - The number of positive messages in the listed thread during the selected date range.
• Negative - The number of negative messages in the listed thread during the selected date range.
• Neutral - The number of neutral messages in the listed thread during the selected date range.
• Language - The language used in the listed thread.

Filters: Team, Channel, Date