onewave-ai Reddit Thread Analyzer
Extract deep insights from Reddit discussions including sentiment, key arguments, and community consensus.
Given a Reddit thread URL or a question about Reddit opinions, analyze the discussion comprehensively to surface meaningful patterns and insights.
Instructions
1. Fetch and Parse Thread Data
Use WebFetch to load the Reddit thread and extract:
- Post title, body, author, score, and timestamp
- All comments (not just top-level)
- Comment scores, awards, and timestamps
- Note verified contributors or expert flair
2. Analyze Overall Sentiment
Determine the dominant sentiment and emotional tone:
- Overall sentiment: Positive, negative, neutral, or mixed
- Sentiment distribution: Approximate percentages
- Emotional tone: Excited, frustrated, skeptical, supportive, angry, enthusiastic
- Shift over time: Note if sentiment changes throughout discussion
3. Extract Key Arguments
Identify the most impactful points:
Top Arguments in Favor (3-5 points):
- Quote the argument
- Note comment score
- Identify supporting evidence or reasoning
Top Arguments Against (3-5 points):
- Quote the argument
- Note comment score
- Identify counter-points and rebuttals
Expert or Verified Opinions:
- Highlight comments from verified experts
- Note OP responses and clarifications
4. Find Consensus Points
Determine what the community agrees on:
- Points with broad agreement (high scores, no controversy)
- Emerging patterns across multiple comments
- Common ground between opposing viewpoints
5. Identify Controversial Topics
Flag heavily debated points:
- Topics with mixed upvotes/downvotes
- Arguments that sparked long comment chains
- Divisive issues where community is split
6. Provide Structured Analysis
Format the analysis clearly:
# Reddit Analysis: [Thread Title]
## Executive Summary
[2-3 sentence overview of the discussion and main takeaway]
## Overall Sentiment
- **Dominant Sentiment**: Positive/Negative/Neutral/Mixed (X%)
- **Emotional Tone**: [excited/frustrated/skeptical/etc.]
- **Community Alignment**: High/Medium/Low
## Top Arguments
### In Favor
1. **[Main point]** (+XXX score)
> "[Direct quote from comment]"
- [Brief explanation of reasoning]
2. **[Main point]** (+XXX score)
> "[Direct quote]"
### Against
1. **[Main point]** (+XXX score)
> "[Direct quote]"
## Community Consensus
- [Point most people agree on]
- [Another consensus point]
## Controversial Topics
- [Divisive issue] - Community split roughly 50/50
- [Another debate point]
## Notable Insights
- **Expert Opinion**: [Quote from verified expert] (+XXX)
- **Surprising Take**: [Unexpected perspective that gained traction]
- **Most Helpful**: [Most practical or actionable advice]
## Key Quotes
> "[Memorable quote]" - u/username (+XXX score)
> "[Another impactful quote]" - u/username (+XXX score)
## Discussion Quality
- Civility: High/Medium/Low
- Depth: Superficial/Moderate/Deep
- Evidence-based: Yes/No/Mixed
Best Practices
- Focus on highly upvoted comments for consensus
- Include exact scores to show community agreement level
- Quote directly rather than paraphrasing
- Preserve nuance - avoid oversimplifying complex debates
- Note OP responses - original poster often adds important context
- Distinguish facts from opinions clearly
- Highlight constructive vs. unproductive discussions
- Consider recency - early comments may be less informed than later ones
Example Analysis
User: "What does Reddit think about the new iPhone?"
Analysis steps:
- Fetch r/apple or r/iPhone thread
- Analyze 300+ comments
- Determine sentiment: Mixed (55% positive, 45% negative)
- Extract top pros: Camera improvements (+450), Performance (+380)
- Extract top cons: High price (+420), Incremental updates (+390)
- Note consensus: Good phone, but expensive for what you get
- Identify controversy: Whether it's worth upgrading from iPhone 14
- Surface expert opinions from tech reviewers
- Deliver structured report with quotes and scores
Remember: Focus on substance over noise. Prioritize well-reasoned arguments over emotional reactions.