IqScreenr

Analyzes tweet text and displays estimated verbal IQ scores with color-coded badges

IQScreenr is a privacy-first browser extension that analyzes Twitter/X tweets in real-time and displays estimated verbal IQ scores using research-validated linguistic analysis. ✨ KEY FEATURES • Real-Time Analysis: Automatically analyzes tweets as you scroll through your Twitter/X feed • IQ Scoring: Estimates verbal IQ from 60-145+ based on comprehensive linguistic analysis • Confidence-Based Colors: Visual gradient indicators from red (low confidence) to green (high confidence) • Privacy-First: All processing happens client-side in your browser - no data sent anywhere • Interactive Game Mode: IqGuessr - Guess the IQ of tweets before revealing scores • Smart Filtering: IqFiltr - Filter tweets by IQ range to focus on specific content quality • Developer Mode: Press CTRL+I+Q for detailed debugging and analysis breakdowns • Hover Details: Comprehensive linguistic breakdown on badge hover 🔬 RESEARCH-VALIDATED METHODOLOGY IQScreenr uses a research-validated estimator that analyzes four key dimensions of written language: 1. Vocabulary Sophistication (35-45% weight) - Uses Age of Acquisition (AoA) ratings from a 31,766-word dictionary - Higher AoA = words learned later in life = more sophisticated vocabulary - Based on research from Kuperman et al. (2012) and Nnamoko et al. (2024) 2. Lexical Diversity (25% weight) - Analyzes Type-Token Ratio (TTR), Mean Segmental TTR (MSTTR), MTLD, and Yule's K - Higher diversity = more varied vocabulary = higher IQ indicator - Research-validated correlation: r = 0.40 3. Sentence Complexity (15-20% weight) - Analyzes average words per sentence with optimality factors - Moderate complexity is optimal (extremely long sentences aren't always better) - Twitter-adjusted baseline accounts for character limits 4. Grammatical Precision (15-20% weight) - Approximates dependency depth from punctuation patterns, clauses, and sentence structure - Analyzes punctuation entropy, subordinate clauses, and connective density - Research-validated correlation: r = 0.45 🎨 UNDERSTANDING THE SCORES Badge colors reflect confidence levels (0-100%), not IQ scores: • Red (0-30%): Low confidence - estimate may be inaccurate • Yellow (30-50%): Moderate confidence • Green (50-100%): High confidence - reliable estimate IQ scores range from approximately 60-145+: • 60-85: Simple, straightforward language with basic vocabulary • 85-105: Average complexity, typical of general population • 105-125: Above average, sophisticated vocabulary and structure • 125-145: High complexity, advanced vocabulary and complex sentence structures • 145+: Exceptional complexity, rare sophisticated writing patterns ⚙️ CUSTOMIZATION OPTIONS • Toggle Badges: Show/hide IQ scores on demand • Adjustable Scale: Customize minimum and maximum IQ display range (default: 60-145) • Confidence Display: Badge colors always reflect confidence levels • Linguistic Breakdown: Enable/disable detailed analysis tooltips • Cache Management: Clear cached scores for recalculation 🔒 PRIVACY & SECURITY IQScreenr is privacy-first: • ✅ 100% Client-Side Processing: All analysis happens in your browser • ✅ No Data Collection: No tweets, scores, or personal data are sent anywhere • ✅ No Tracking: No analytics, no telemetry, no external requests • ✅ Local Storage Only: Settings and cache stored locally in your browser • ✅ Open Source: Full code available for inspection Your data stays on your device. Always. ⚠️ IMPORTANT DISCLAIMER IQScreenr provides estimates based on linguistic analysis, not actual IQ test results. These scores: • Are based on written language patterns only • May not reflect actual intelligence accurately • Should not be used for important decisions • Are for entertainment and educational purposes Use responsibly and remember: intelligence is multifaceted and cannot be fully captured by text analysis alone. 📚 RESEARCH SOURCES • Kuperman, V., Stadthagen-Gonzalez, H., & Brysbaert, M. (2012). Age-of-acquisition ratings for 30,000 English words. Behavior Research Methods, 44(4), 978-990. • Nnamoko et al. (2024). Age of Acquisition proxies for vocabulary sophistication estimation. • Wolfram (2025). Linguistic complexity and intelligence correlation. • Abramov (2018). Type-Token Ratio and lexical diversity metrics. • Hendrix, A., & Yampolskiy, R. (2017). Automated IQ Estimation from Writing Samples. 🌐 SUPPORT For questions, issues, or feature requests, visit: https://iqscreenr.win