Documentation Index
Fetch the complete documentation index at: https://docs.threadlytics.io/llms.txt
Use this file to discover all available pages before exploring further.
Overview
The Sentiment Analysis page breaks down how Reddit users feel about your brand and competitors. It shows the overall sentiment distribution and provides a per-keyword breakdown so you can see exactly which terms are driving positive or negative conversation.
Filters
| Filter | Options |
|---|
| Keyword Type | All Types, Brand only, or Competitor only |
Brand Sentiment Analysis
A donut/pie chart showing the overall split of sentiment across all mentions that match the active filter.
Sentiment categories:
| Category | Color | Meaning |
|---|
| Positive | Green | Posts and comments with a favorable tone toward the keyword |
| Neutral | Yellow / Grey | Informational or ambiguous content |
| Negative | Red | Posts and comments with a critical or unfavorable tone |
Sentiment by Keyword
A sortable table showing the sentiment breakdown for every individual tracked keyword that matches the current filter.
Table Columns
| Column | Description |
|---|
| Keyword | The tracked term, with a color-coded type badge (Brand / Competitor / Industry) |
| Total Mentions | Total number of Reddit posts and comments matched |
| Positive | Count and percentage of positive mentions |
| Neutral | Count and percentage of neutral mentions |
| Negative | Count and percentage of negative mentions |
How Sentiment Is Determined
Threadlytics uses a simple keyword matching approach to analyze sentiment. Each mention is analyzed for the presence of positive and negative signal words within the content.
- Positive: words like amazing, great, love, recommend, helpful
- Negative: words like terrible, bad, hate, bug, expensive, slow
- Neutral/Question: words like what, how, why, advice, opinion
It counts matches, calculates ratios, and classifies as positive/negative/neutral. A sentiment score between -1 and +1 is also stored. The resulting score determines whether the post is classified as Positive, Neutral, or Negative.
It works well for clear-cut posts, but may misclassify sarcasm, complex opinions, or posts where the brand is mentioned alongside unrelated sentiment words.
This analysis runs automatically during keyword refresh and is stored alongside each mention.
