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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.

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Filters

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Brand Sentiment Analysis

A donut/pie chart showing the overall split of sentiment across all mentions that match the active filter. Sentiment categories: Below the chart, three stat cards display the raw mention count and percentage for each sentiment category.

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Sentiment by Keyword

A sortable table showing the sentiment breakdown for every individual tracked keyword that matches the current filter.

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Table Columns

Click any column header to sort the table by that metric. Sorting by Negative % quickly surfaces the keywords generating the most criticism.

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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.