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Sentiment Analysis uses AI to examine threads across your application, detect conversation topics, classify each mention as positive, neutral, or negative, and produce summaries with actionable recommendations — all without manual tagging or surveys.

Features

Sentiment Scoring

Overall sentiment score (0–100) with period-over-period comparison to track community health trends

Topic Detection

AI automatically identifies and tracks conversation topics across all analyzed threads

AI Summaries

Per-topic summaries of negative, neutral, and positive mentions with actionable recommendations

Thread-Level Analysis

Browse individual analyzed threads with detected topics and full conversation context

Trend Charts

Sentiment over time and mentions over time visualizations with percentage and absolute views

Topic Configuration

Define custom topics for the AI to track, with full control over additions and removals

Getting Started

RequirementDetails
AccessDashboard login with Moderator or Analyst permission
Feature enablementSentiment Analysis enabled on your network (contact support if not visible)
CreditsAnalysis uses thread credits — monitor usage in the credit banner
NavigationDashboard → Social Insights → Sentiment analysis
Need Sentiment Analysis enabled? Email [email protected] with your network ID.

Credit & Analysis Coverage

At the top of the page a credit banner shows how many threads were analyzed out of your total credit allocation for the selected date range.
  • Coverage percentage — A circular gauge (e.g., 95%) indicates analysis completeness.
  • Thread count — For example, 9520 of 10000 threads that matched the filters were analyzed.
  • Manage credit — Click to view or adjust your credit allocation.
If the number of threads created or updated in your application exceeds your credit, not all threads will be analyzed by AI.

Filtering & Date Range

Date Range

Use the date picker in the top-right corner to select the analysis period. Comparison metrics (e.g., +2 pts, +80%) automatically reference the equivalent prior period.

Filters

Click the Filter button to narrow analysis scope:
FilterDescription
CommunityFilter by one or more communities using Matches any of logic
User tagFilter by user tags to focus on specific user segments
1

Open Filter Panel

Click the Filter button next to the date picker.
2

Select Filters

Choose communities and/or user tags from the dropdowns.
3

Apply

Click Apply to refresh all tabs with the filtered data. Use Clear all to reset.

Overview Tab

The Overview tab provides a high-level snapshot of sentiment across your entire application (or filtered scope).

Key Metrics

Sentiment Score

Score from 0–100 indicating overall community sentiment. Labeled Positive, Neutral, or Negative. Shows point change vs. the prior comparison period.

Total Topics Detected

Number of distinct topics the AI identified in the selected period. Shows percentage change vs. prior period.

Total Mentions

Aggregate count of all topic mentions across analyzed threads. Shows percentage change vs. prior period.

Top Negative & Positive Topics

Two side-by-side panels highlight the topics with the highest concentration of negative and positive sentiment:
  • Top topic callout — Shows the topic name, total mention count, and what percentage was negative or positive.
  • Horizontal bar chart — Ranks the top 5 topics by total mentions. Negative chart bars are shown in red/orange; positive chart bars are shown in blue.
Hover over any bar in the chart to see a breakdown of negative, neutral, and positive mention counts for that topic.

Sentiment Breakdown

A donut chart showing the distribution of all mentions across three categories:
  • Negative mentions (red) — count and percentage
  • Neutral mentions (orange/yellow) — count and percentage
  • Positive mentions (blue) — count and percentage

Sentiment Over Time

A line chart tracking how sentiment proportions change over the selected date range. Toggle between:
  • Percentage — Shows each sentiment category as a percentage of daily total
  • Number — Shows absolute mention counts per day

Topic Analysis Tab

The Topic Analysis tab provides a sortable table of all detected topics with detailed metrics.
ColumnDescription
TopicName of the detected topic
MentionsTotal number of mentions (sortable)
ChangePercentage change vs. the prior comparison period (sortable). Shows No baseline for newly detected topics
SentimentStacked horizontal bar showing negative %, neutral %, and positive %
ActionView insights link to drill into the topic detail page

Topic Detail Page

Clicking View insights on any topic opens a dedicated page with deep analysis for that specific topic.
  • Sentiment score — Topic-specific score (0–100) with comparison to prior period
  • Total mentions — Mention count for this topic with percentage change
The right-side panel provides AI-generated insights organized by sentiment:
  • Negative mentions — Summary of key negative themes with a View threads button to see source posts
  • Neutral mentions — Summary of neutral/mixed feedback
  • Positive mentions — Summary of positive themes and praise
  • Recommendation — Actionable suggestions derived from the analysis (e.g., “Address concerns urgently. Consider user feedback surveys.”)
Line chart showing how mention volume for this topic changed over the selected date range.
Donut chart showing negative, neutral, and positive distribution for this specific topic.
Line chart with Percentage and Number toggle showing sentiment trend for this topic.

Analyzed Threads Tab

The Analyzed Threads tab lets you browse the actual posts and comments that were analyzed.

Thread List (Left Panel)

A scrollable list of analyzed threads showing:
  • Author name and avatar
  • Timestamp (e.g., 2 Apr 2026, 17:35)
  • Community name where the thread was posted
  • Content preview — Truncated text of the original post
  • Engagement — Reaction count and comment count

Thread Detail (Right Panel)

Selecting a thread displays:
  • Topic detected — Tags showing which topics the AI identified in this thread (editable via tag icons)
  • Full post content — Complete text including hashtags, mentions, and links
  • Engagement metrics — Reactions and comments count
  • Comment thread — All comments and replies with author, timestamp, and nested replies
Use the Analyzed Threads tab to validate AI-generated summaries by reviewing the actual source posts that informed them.

Topic Configuration

Access Topic Configuration via the settings gear icon (⚙) in the top-right corner of the Sentiment Analysis page.
Changes to the configuration will not affect analyses that have already been performed. New configurations take effect for analyses starting from the date they were added.

Managing Topics

1

Open Configuration

Click the settings gear icon on the Sentiment Analysis page to navigate to Topic configuration.
2

Review Existing Topics

View the table of configured topics with their names and date added. The table is sortable by Date added.
3

Add a Topic

Click + Add topic to define a new topic for the AI to track in future analyses.
4

Remove a Topic

Click the delete icon (🗑) in the Action column to remove a topic from future analyses.
Removing a topic stops future analysis for that topic but does not delete historical data. Historical results remain available for the date range when the topic was active.

Daily Operational Workflow

1

Check Overview

Open Sentiment Analysis and review the three KPI cards for any significant changes in sentiment score, topic count, or mention volume.
2

Identify Problem Areas

Check the Top negative topics panel. If any topic shows a high negative percentage, click through to investigate.
3

Review AI Summaries

On the topic detail page, read the AI Summary panel’s negative mentions and recommendations.
4

Validate with Source Data

Click View threads to review actual posts behind the AI summaries. Confirm findings before taking action.
5

Monitor Trends

Use the Sentiment over time chart to check whether negative sentiment is a spike or sustained trend.
6

Take Action

Convert high-confidence recommendations into backlog tickets, content changes, or moderation actions.

Best Practices

  • Monitor the credit banner regularly — if coverage drops below 80%, consider applying filters to prioritize high-value communities.
  • Use community and user tag filters to focus credits on segments that matter most.
  • Contact support to increase credit limits if your application consistently exceeds allocation.
  • Start with 5–10 broad topics and refine as patterns emerge from the AI analysis.
  • Review the Topic Analysis tab monthly to identify if any configured topics have zero mentions — consider replacing them.
  • Add new topics when you notice emerging themes in the Analyzed Threads tab.
  • Remember that topic changes only affect future analyses — historical data remains unchanged.
  • A sentiment score of 50 indicates perfectly balanced sentiment — not necessarily good or bad.
  • Focus on change over time rather than absolute scores — a 5+ point drop warrants investigation.
  • Cross-reference sentiment shifts with product releases, incidents, or campaigns for causal analysis.
  • Low mention volumes can cause score volatility — set a minimum threshold before acting on changes.
  • Always validate AI summaries by reviewing source threads before escalating issues.
  • Use the Recommendation section as a starting point, not a final directive — apply business context.
  • Compare negative topics against positive topics to understand relative priority.
  • Track whether actions taken improve sentiment in subsequent analysis periods.

AI Research

Ad-hoc natural language analysis across community conversations

Social Analytics

Quantitative engagement and usage metrics for social features

Raw Data Export

Export raw data for deeper custom analysis and reporting