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Overview

Narrative Radar is Argument Cartographer’s “Head-Up Display” for the information ecosystem - a curated feed of high-impact, trending topics that have been pre-analyzed for logical integrity and public sentiment.
Key Benefit: Explore complex debates instantly without waiting for AI processing or consuming your API quota.

Curated Topics

Expert-selected controversial debates and breaking news

Pre-Generated

Analyses ready instantly - no wait time

Always Fresh

Updated daily as news develops

Free Access

Available to all users without API costs

How Narrative Radar Works

1

Topic Curation

Editorial team or automated algorithms identify trending topics based on:
  • News velocity (rapid coverage growth)
  • Social engagement (Twitter discussion volume)
  • Public interest (search trends)
  • Controversy level (polarized viewpoints)
2

Pre-Analysis

Before topics appear in Radar, they’re fully analyzed:
  • Web search across trusted sources
  • Argument blueprint generation
  • Fallacy detection
  • Social pulse gathering
  • Credibility scoring
3

Publication

Completed analyses are published to the Radar feed with metadata:
  • Title and description
  • Thumbnail image
  • Credibility score preview
  • Source count
  • Last updated timestamp
4

User Access

Users browse the feed and click to explore full analysis

Radar Feed Interface

The Radar page (/radar) displays a grid of topic cards:

Topic Card Components

  • Thumbnail - Representative image for the topic
  • Title - Clear, neutral phrasing of the debate
  • Description - 1-2 sentence summary
  • Badges - Category tags (Politics, Technology, Science, etc.)
  • Freshness Indicator - “Updated 2 hours ago”
const RadarTopicCard = ({ topic }) => (
  <Card className="radar-card hover:shadow-lg transition-shadow">
    <CardImage src={topic.thumbnail} alt={topic.title} />
    
    <CardContent>
      <div className="flex items-start justify-between">
        <h3 className="font-bold text-lg">{topic.title}</h3>
        <CredibilityBadge score={topic.credibilityScore} />
      </div>
      
      <p className="text-muted-foreground">{topic.description}</p>
      
      <div className="flex gap-2 flex-wrap mt-2">
        {topic.categories.map(cat => (
          <Badge variant="secondary">{cat}</Badge>
        ))}
      </div>
      
      <div className="flex items-center gap-4 mt-4 text-sm">
        <Metric icon="newspaper">{topic.sourceCount} sources</Metric>
        <Metric icon="warning">{topic.fallacyCount} fallacies</Metric>
        <Metric icon="clock">{formatRelativeTime(topic.updatedAt)}</Metric>
      </div>
    </CardContent>
    
    <CardFooter>
      <Button asChild className="w-full">
        <Link href={`/radar/${topic.id}`}>Explore Analysis</Link>
      </Button>
    </CardFooter>
  </Card>
);

Topic Selection Criteria

Not every news story makes it to the Radar. Topics are selected based on:

Controversy Level

1

Genuine Debate

Topic must have legitimate arguments on multiple sides - not one-sided issues
2

Polarization

Significant public disagreement or partisan split
3

Complexity

Nuanced issue with multiple dimensions (economic, ethical, practical, etc.)

Public Impact

  • Relevance: Affects large populations
  • Timeliness: Currently in the news cycle
  • Searchability: People are actively seeking information

Source Availability

  • Coverage Depth: At least 8-10 quality sources available
  • Diversity: Sources span ideological spectrum
  • Recency: Fresh articles (< 30 days old for most topics)
Example Good Topics:
  • “Should AI art be copyrightable?”
  • “Universal Basic Income: Economic solution or fiscal disaster?”
  • “COVID-19 vaccine mandates: Public health vs personal freedom”
Example Poor Topics:
  • “Is murder wrong?” (no genuine debate)
  • “My neighbor’s fence dispute” (not public interest)
  • “The 2015 dress color debate” (trivial)

Categorization System

Radar topics are tagged with multiple categories for easy filtering:
  • Electoral politics
  • Policy debates
  • Governance issues
  • International relations
Users can filter the Radar feed:
const [selectedCategory, setSelectedCategory] = useState<string | null>(null);
const [minCredibility, setMinCredibility] = useState(0);
const [sortBy, setSortBy] = useState<'newest' | 'credibility' | 'engagement'>('newest');

const filteredTopics = topics
  .filter(t => !selectedCategory || t.categories.includes(selectedCategory))
  .filter(t => t.credibilityScore >= minCredibility)
  .sort((a, b) => {
    switch (sortBy) {
      case 'newest': return b.updatedAt - a.updatedAt;
      case 'credibility': return b.credibilityScore - a.credibilityScore;
      case 'engagement': return b.tweetCount - a.tweetCount;
    }
  });
Filter options:
  • Category - Show only specific categories
  • Credibility - Minimum score threshold (1-10)
  • Freshness - Last 24h, Last week, Last month
  • Sort - Newest, Highest credibility, Most engagement

Update Frequency

Radar topics are dynamic and evolve:
Update frequency: Every 2-6 hoursFast-moving stories are re-analyzed as new sources emerge:
  • New articles incorporated
  • Social sentiment refreshed
  • Fallacies re-evaluated
Users see “Updated 2 hours ago” indicators

Data Structure

Radar topics are stored in Firestore:
interface RadarTopic {
  id: string;
  title: string;
  description: string;
  thumbnail: string;
  categories: string[];
  
  // Analysis data
  blueprint: ArgumentNode[];
  credibilityScore: number;
  fallacies: DetectedFallacy[];
  tweets: Tweet[];
  socialPulse: string;
  
  // Metadata
  sourceCount: number;
  fallacyCount: number;
  tweetCount: number;
  
  // Timestamps
  createdAt: Timestamp;
  updatedAt: Timestamp;
  
  // Curation
  curatedBy?: string; // Editor or "auto"
  featured: boolean; // Show in hero section
  archived: boolean; // Historical topic
}
Firestore path: /radarTopics/{topicId}
Radar topics are publicly readable (unlike user analyses) to enable sharing and SEO.

Benefits for Users

Zero Wait Time

Analyses load instantly - no 30-second processing delay

API Credits Saved

Exploring Radar doesn’t consume your Firecrawl/Twitter quota

Quality Curation

Editorial oversight ensures important, well-sourced topics

Educational Value

See how current events map to logical structures

Use Cases

When major news breaks, Radar provides instant logical breakdown before misinformation spreads.Example: Within hours of a policy announcement, users can explore:
  • Official justifications
  • Expert criticisms
  • Historical precedents
  • Potential fallacies in political rhetoric
Teachers can assign Radar topics for critical thinking exercises:
  • “Analyze the fallacies in this debate”
  • “Compare the strength of evidence on each side”
  • “Track how the narrative evolved over time”
Journalists and researchers use Radar as a launchpad:
  • Identify key sources quickly
  • See what questions haven’t been answered
  • Find gaps in existing coverage
Users facing important choices (voting, career, investments) can:
  • See both sides of relevant debates
  • Evaluate evidence quality
  • Identify manipulative rhetoric

Curation Workflow

For administrators managing Radar content:
1

Topic Selection

Identify trending topics via:
  • News aggregators (Google News, AllSides)
  • Social listening (Twitter trending)
  • User requests/votes
2

Analysis Generation

Run standard analysis flow programmatically:
npm run generate-radar-topic "AI regulation debate"
3

Quality Review

Human reviewer checks:
  • Blueprint accuracy
  • Fallacy detection validity
  • Source diversity
  • Neutrality of summary
4

Metadata Addition

Add:
  • Thumbnail image
  • Category tags
  • Featured flag (if high priority)
  • Description text
5

Publication

Publish to /radarTopics collection - appears in feed immediately

Future Enhancements

Planned features for Narrative Radar:

User Voting

Community votes to prioritize which topics get analyzed next

Custom Alerts

Subscribe to categories and get notified of new analyses

Comparative Timeline

See how arguments evolved as events unfolded

Debate Forecasting

Predict which narratives will gain traction based on patterns

Next Steps

Using the Radar

Detailed guide to exploring Radar topics

Social Pulse

Understand Twitter sentiment integration

Credibility Scoring

Learn how topics are scored

Creating Analyses

Create your own custom analyses

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