The Natural Language Analysis report for Teams utilizes advanced AI features like natural language processing (NLP) to analyze Teams content, detect key phrases and themes, understand multilingual conversations, and analyze sentiment trends. These capabilities enhance understanding, promote collaboration, help gauge satisfaction and ensure decisions are well-informed and data-driven.
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.
Messages Sentiment Trend
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