AI reads the comment together with the post and the full thread
The meaning of a short comment often depends on the post and earlier reactions. The module preserves this context.
Questions under a family weekend post
Several people ask about children’s stay conditions, while one comment criticises the unclear wording about the surcharge.
Topics and response order
The system groups questions about the same condition, separates criticism from a simple request for information and flags unanswered comments.
- most common topics under the post
- reactions to a specific content element
- threads requiring a response
Every comment analysed in the context of the post
The module identifies public reactions to brand content and organises developing conversations. It does not treat a single word as a complete statement without context.
Groups reactions
It brings together questions, praise, complaints and recurring topics across platforms and posts.
Reads the full thread
It considers the post content, the parent comment and earlier replies.
Detects growth
It highlights discussions where new comments or reactions are appearing quickly.
How is a public discussion analysed?
Collecting the thread
The panel provides the post, comments, replies, platform, time and brand response status.
Identifying meaning
AI determines the topic and type of comment in the context of the full conversation.
Assessing momentum
The system measures the increase in comments and detects rapidly developing threads.
Sending to the queue
Questions and issues requiring a response receive a topic, priority and source link.
The post and earlier replies are part of the comment’s meaning
Analysis should not separate comments from their context. Team input can help identify local abbreviations, jokes and situations requiring care.
What does AI use?
- post or publication content
- comment and earlier replies
- platform, date and thread momentum
- optional brand and team context
What does the team receive?
- most common comment topics
- reactions to specific brand content
- list of questions and threads requiring a response
Automated classification does not replace knowledge of your community
Irony, jokes and local context can be ambiguous. The team can correct the classification and provide the right interpretation.
The user selects profiles and the analysis period, reviews ambiguous comments and decides on the next response.
The module does not publish responses, moderate discussions, delete comments or automatically treat a critical comment as a crisis.
A clear view of reactions to your brand communication
Recurring information needs do not get lost among the comments.
The team can see which elements of a post generated interest or confusion.
A growing discussion is brought to the team’s attention before it remains unanswered for too long.
Comments go to a shared reputation panel
The Central Reputation Panel brings together public comments and response statuses. The AI platform analyses their topics and momentum.
Related process elements
Frequently asked questions
Does the module analyse a comment without the post content?
It should not. The post content and earlier replies are an important part of the context.
Does it recognise irony and jokes?
It may flag them, but ambiguous comments should be checked by a person.
Does it measure how quickly a discussion is developing?
Yes. It can highlight threads where comments or reactions are increasing quickly.
Does it automatically respond to people?
No. The analysis passes comments to the next modules and the response queue.