Octolens automatically analyzes the sentiment of every mention it finds, classifying each post as positive, neutral, or negative. This helps you quickly identify praise, complaints, and everything in between.Documentation Index
Fetch the complete documentation index at: https://octolens.com/docs/llms.txt
Use this file to discover all available pages before exploring further.
How sentiment is used
Sentiment is available as a filter throughout Octolens:- In any feed: filter mentions by sentiment to focus on what matters most. See Feeds.
- As a feed filter: build feeds based on sentiment. For example, a feed for only positive or negative mentions about your brand.
- In destinations: any sentiment-scoped feed can be sent to Slack, email, or a webhook. See Destinations.
- On the Dashboard: break the Mentions over time chart down by sentiment to see the positive/neutral/negative split day by day. See Dashboard.
- Via MCP: ask the MCP server about sentiment trends in natural language.
- In the API: filter mentions by sentiment programmatically. See API Reference.
Sentiment values
| Value | Meaning |
|---|---|
| Positive | The post expresses approval, praise, satisfaction, or enthusiasm |
| Neutral | The post is informational, factual, or doesn’t express strong emotion |
| Negative | The post expresses frustration, complaint, dissatisfaction, or criticism |
Sentiment is detected automatically by the AI. To improve accuracy, make sure your Company Context is filled in so the AI can better understand what’s relevant to your business.