Outil complet d'analyse de texte

Here is the HTML code for a comprehensive text analysis tool. It's a single, self-contained webpage with a clean interface for input, analysis, and reporting. ```html LinguaLab · text analysis suite * { margin: 0; padding: 0; box-sizing: border-box; font-family: 'Inter', system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; } body { background: #f4f7fc; padding: 2rem 1.5rem; display: flex; justify-content: center; align-items: flex-start; min-height: 100vh; } .app-wrapper { max-width: 1400px; width: 100%; background: white; border-radius: 2rem; box-shadow: 0 25px 50px -12px rgba(0,0,0,0.15); padding: 2rem 2.5rem; } h1 { font-size: 2.2rem; font-weight: 600; letter-spacing: -0.02em; color: #0b1e33; display: flex; align-items: center; gap: 0.75rem; margin-bottom: 0.5rem; } h1 i { color: #2a6df4; font-size: 2rem; } .subhead { color: #4a5b6e; margin-bottom: 2rem; font-size: 1rem; border-left: 4px solid #2a6df4; padding-left: 1rem; } .grid-2col { display: grid; grid-template-columns: 1fr 1fr; gap: 2rem; } .input-panel { background: #f9fbfe; border-radius: 1.5rem; padding: 1.5rem; border: 1px solid #e2e9f2; } .input-panel textarea { width: 100%; height: 280px; border: 1px solid #d0dcec; border-radius: 1rem; padding: 1.2rem; font-size: 1rem; line-height: 1.6; background: white; resize: vertical; transition: 0.2s; } .input-panel textarea:focus { outline: none; border-color: #2a6df4; box-shadow: 0 0 0 3px rgba(42,109,244,0.15); } .toolbar { display: flex; flex-wrap: wrap; gap: 0.6rem; margin-top: 1rem; align-items: center; } .btn { background: white; border: 1px solid #cbd6e4; padding: 0.5rem 1rem; border-radius: 2rem; font-size: 0.85rem; font-weight: 500; cursor: pointer; transition: 0.15s; display: inline-flex; align-items: center; gap: 0.4rem; color: #1e2f44; } .btn:hover { background: #eef3fa; border-color: #2a6df4; } .btn-primary { background: #2a6df4; border-color: #2a6df4; color: white; } .btn-primary:hover { background: #1d5adf; } .btn-sm { padding: 0.3rem 0.8rem; font-size: 0.8rem; } .results-panel { background: #f9fbfe; border-radius: 1.5rem; padding: 1.5rem; border: 1px solid #e2e9f2; } .metric-grid { display: grid; grid-template-columns: repeat(3, 1fr); gap: 0.8rem; margin-bottom: 1.5rem; } .metric-card { background: white; border-radius: 1rem; padding: 0.8rem 0.5rem; text-align: center; box-shadow: 0 2px 6px rgba(0,0,0,0.02); border: 1px solid #e6edf5; } .metric-card .value { font-size: 1.8rem; font-weight: 700; color: #0b1e33; } .metric-card .label { font-size: 0.7rem; text-transform: uppercase; letter-spacing: 0.04em; color: #5f7186; } .section-title { font-weight: 600; font-size: 1rem; color: #0b1e33; margin: 1.2rem 0 0.6rem 0; border-bottom: 1px dashed #cbd6e4; padding-bottom: 0.3rem; display: flex; align-items: center; gap: 0.5rem; } .readability-row { display: flex; flex-wrap: wrap; gap: 1.5rem; background: white; padding: 0.8rem 1rem; border-radius: 1rem; border: 1px solid #e6edf5; } .readability-item { display: flex; align-items: baseline; gap: 0.5rem; } .readability-item strong { font-size: 1.2rem; color: #1e3a5f; } .keyword-visual { background: white; border-radius: 1rem; padding: 0.8rem; border: 1px solid #e6edf5; } .keyword-bar { display: flex; align-items: center; gap: 0.5rem; margin-bottom: 0.4rem; } .keyword-bar .kw { min-width: 100px; font-size: 0.85rem; font-weight: 500; } .bar-bg { flex: 1; height: 8px; background: #e2e9f2; border-radius: 20px; overflow: hidden; } .bar-fill { height: 100%; background: #2a6df4; border-radius: 20px; } .kw-percent { font-size: 0.75rem; color: #4a5b6e; width: 45px; text-align: right; } .sentiment-tag { display: inline-block; background: #eaf2ff; padding: 0.3rem 1rem; border-radius: 30px; font-size: 0.9rem; font-weight: 500; margin-right: 0.5rem; } .suggestion-box { background: #fff8e7; border-left: 4px solid #f5b942; padding: 0.6rem 1rem; border-radius: 0.5rem; font-size: 0.85rem; margin-top: 0.5rem; } .compare-area { display: flex; gap: 0.8rem; align-items: center; margin-top: 0.5rem; } .compare-area input { flex: 1; border: 1px solid #d0dcec; border-radius: 2rem; padding: 0.5rem 1rem; font-size: 0.85rem; } .footer-export { display: flex; justify-content: flex-end; gap: 0.8rem; margin-top: 1.5rem; border-top: 1px solid #e2e9f2; padding-top: 1.2rem; } .language-badge { background: #e6f0ff; padding: 0.2rem 0.8rem; border-radius: 30px; font-size: 0.8rem; font-weight: 500; display: inline-block; } .detected-lang { margin-left: 0.5rem; } @media (max-width: 900px) { .grid-2col { grid-template-columns: 1fr; } .app-wrapper { padding: 1.5rem; } } LinguaLab comprehensive text analysis · readability · sentiment · keywords · comparison The quick brown fox jumps over the lazy dog. This is a simple text to demonstrate analysis. The quick brown fox is agile. We test readability and sentiment. Amazing day, wonderful experience! Analyze Clear Clean UPPER lower auto Spelling & grammar (demo) Suggestions: "quick" → "quick" (no change) · "fox" ok Text comparison Similarity 0 words 0 chars 0 min read Readability Flesch-Kincaid: -- SMOG: -- Coleman-Liau: -- Keyword density quick 60% fox 40% Sentiment & tone Positive joy, excitement Export report Format text (function() { // DOM elements const textarea = document.getElementById('mainText'); const wordCountEl = document.getElementById('wordCount'); const charCountEl = document.getElementById('charCount'); const readTimeEl = document.getElementById('readTime'); const fkEl = document.getElementById('fkScore'); const smogEl = document.getElementById('smogScore'); const clEl = document.getElementById('clScore'); const keywordContainer = document.getElementById('keywordContainer'); const sentimentTag = document.getElementById('sentimentTag'); const toneWords = document.getElementById('toneWords'); const langDisplay = document.getElementById('langDisplay'); const grammarSuggestion = document.getElementById('grammarSuggestion'); const similarityResult = document.getElementById('similarityResult'); // helper: word count function getWords(text) { return text.trim().split(/\s+/).filter(w => w.length > 0); } // syllable counter (approx) function countSyllables(word) { word = word.toLowerCase().replace(/[^a-z]/g, ''); if (!word) return 0; let count = 0; let prevVowel = false; const vowels = new Set(['a','e','i','o','u','y']); for (let i=0; i<word.length; i++) { const ch = word[i]; if (vowels.has(ch)) { if (!prevVowel) count++; prevVowel = true; } else prevVowel = false; } if (count === 0) count = 1; return count; } // Flesch-Kincaid grade level function fleschKincaid(text) { const words = getWords(text); const sentences = text.split(/[.!?]+/).filter(s => s.trim().length > 0).length || 1; const syllables = words.reduce((sum, w) => sum + countSyllables(w), 0); if (words.length === 0) return 0; return 0.39 * (words.length / sentences) + 11.8 * (syllables / words.length) - 15.59; } // SMOG index (simplified) function smogIndex(text) { const sentences = text.split(/[.!?]+/).filter(s => s.trim().length > 0).length || 1; const words = getWords(text); const polysyllables = words.filter(w => countSyllables(w) >= 3).length; if (sentences === 0) return 0; return 1.0430 * Math.sqrt(polysyllables * (30 / sentences)) + 3.1291; } // Coleman-Liau index function colemanLiau(text) { const words = getWords(text); if (words.length === 0) return 0; const letters = text.replace(/[^a-zA-Z]/g, '').length; const sentences = text.split(/[.!?]+/).filter(s => s.trim().length > 0).length || 1; const L = (letters / words.length) * 100; const S = (sentences / words.length) * 100; return 0.0588 * L - 0.296 * S - 15.8; } // keyword density (top 5) function keywordDensity(text) { const words = getWords(text.toLowerCase().replace(/[^a-z\s]/g, '')); if (words.length === 0) return []; const freq = {}; words.forEach(w => { if (w.length > 2) freq[w] = (freq[w] || 0) + 1; }); const sorted = Object.entries(freq).sort((a,b) => b[1] - a[1]).slice(0,5); const max = sorted.length ? sorted[0][1] : 1; return sorted.map(([word, count]) => ({ word, count, percent: Math.round((count / max) * 100) })); } // simple sentiment lexicon (demo) function sentimentAnalysis(text) { const positive = ['good', 'great', 'amazing', 'wonderful', 'excellent', 'happy', 'love', 'beautiful', 'nice', 'joy']; const negative = ['bad', 'terrible', 'awful', 'hate', 'sad', 'angry', 'poor', 'horrible', 'ugly']; const words = getWords(text.toLowerCase().replace(/[^a-z\s]/g, '')); let posCount = 0, negCount = 0; words.forEach(w => { if (positive.includes(w)) posCount++; if (negative.includes(w)) negCount++; }); let tone = 'Neutral'; let emoji = 'fa-face-meh'; if (posCount > negCount) { tone = 'Positive'; emoji = 'fa-face-smile'; } else if (negCount > posCount) { tone = 'Negative'; emoji = 'fa-face-frown'; } const toneList = []; if (posCount > 0) toneList.push('joy', 'excitement'); if (negCount > 0) toneList.push('frustration'); if (toneList.length === 0) toneList.push('neutral'); return { tone, emoji, toneWords: toneList.join(', ') }; } // language detection (very basic) function detectLanguage(text) { const sample = text.trim().slice(0, 200); if (/[äöüß]/.test(sample)) return 'German'; if (/[éèêàç]/.test(sample)) return 'French'; if (/[ñ¿¡]/.test(sample)) return 'Spanish'; if (/[а-яА-Я]/.test(sample)) return 'Russian'; return 'English'; } // update all metrics function analyze() { const text = textarea.value; if (!text.trim()) { resetResults(); return; } const words = getWords(text); const charCount = text.length; const wc = words.length; wordCountEl.textContent = wc; charCountEl.textContent = charCount; const readingTime = Math.ceil(wc / 200); // 200 wpm readTimeEl.textContent = readingTime; // readability fkEl.textContent = fleschKincaid(text).toFixed(1); smogEl.textContent = smogIndex(text).toFixed(1); clEl.textContent = colemanLiau(text).toFixed(1); // keywords const kwData = keywordDensity(text); if (kwData.length === 0) { keywordContainer.innerHTML = ' No keywords '; } else { keywordContainer.innerHTML = ''; kwData.forEach(k => { const bar = document.createElement('div'); bar.className = 'keyword-bar'; bar.innerHTML = ` ${k.word} ${k.percent}% `; keywordContainer.appendChild(bar); }); } // sentiment const senti = sentimentAnalysis(text); sentimentTag.innerHTML = ` ${senti.tone}`; toneWords.textContent = senti.toneWords; // language const lang = detectLanguage(text); langDisplay.innerHTML = ` ${lang}`; // grammar suggestion (demo) if (text.includes(' ')) { grammarSuggestion.innerHTML = ' Double spaces detected. Use "Clean" to fix.'; } else { grammarSuggestion.innerHTML = ' No obvious spacing issues. (demo)'; } } function resetResults() { wordCountEl.textContent = '0'; charCountEl.textContent = '0'; readTimeEl.textContent = '0'; fkEl.textContent = '--'; smogEl.textContent = '--'; clEl.textContent = '--'; keywordContainer.innerHTML = ' No data '; sentimentTag.innerHTML = ' Neutral'; toneWords.textContent = 'neutral'; langDisplay.innerHTML = ' auto'; grammarSuggestion.innerHTML = ' Suggestions: none'; } // cleaning tools function cleanText() { let val = textarea.value; val = val.replace(/\s+/g, ' ').trim(); textarea.value = val; analyze(); } // export report function exportReport() { const text = textarea.value; const report = { wordCount: wordCountEl.textContent, charCount: charCountEl.textContent, readingTime: readTimeEl.textContent, fleschKincaid: fkEl.textContent, smog: smogEl.textContent, colemanLiau: clEl.textContent, sentiment: sentimentTag.textContent.trim(), language: langDisplay.textContent.trim(), preview: text.slice(0, 100) }; const blob = new Blob([JSON.stringify(report, null, 2)], { type: 'application/json' }); const url = URL.createObjectURL(blob); const a = document.createElement('a'); a.href = url; a.download = 'analysis-report.json'; a.click(); URL.revokeObjectURL(url); } // similarity (dice coefficient) function similarity(a, b) { if (!a.trim() || !b.trim()) return 0; const setA = new Set(a.toLowerCase().match(/\b\w+\b/g)); const setB = new Set(b.toLowerCase().match(/\b\w+\b/g)); let common = 0; setA.forEach(w => { if (setB.has(w)) common++; }); const total = setA.size + setB.size; return total === 0 ? 0 : (2 * common) / total; } // event listeners document.getElementById('analyzeBtn').addEventListener('click', analyze); document.getElementById('clearBtn').addEventListener('click', () => { textarea.value = ''; resetResults(); }); document.getElementById('trimBtn').addEventListener('click', cleanText); document.getElementById('upperBtn').addEventListener('click', () => { textarea.value = textarea.value.toUpperCase(); analyze(); }); document.getElementById('lowerBtn').addEventListener('click', () => { textarea.value = textarea.value.toLowerCase(); analyze(); }); document.getElementById('exportBtn').addEventListener('click', exportReport); document.getElementById('formatBtn').addEventListener('click', () => { let val = textarea.value; val = val.replace(/[ \t]+/g, ' ').replace(/\n{3,}/g, '\n\n').trim(); textarea.value = val; analyze(); }); document.getElementById('compareBtn').addEventListener('click', () => { const secondText = document.getElementById('compareInput').value; const sim = similarity(textarea.value, secondText); similarityResult.innerHTML = `Similarity (Dice): ${(sim * 100).toFixed(1)}% `; }); // initial analysis analyze(); })(); ``` ### Core Analysis Features You can paste or type text to see a detailed breakdown across several key areas. The tool is designed to give you a quick, multi-dimensional overview of your text's characteristics. - **Input & Text Tools**: The left panel includes a large text area. Use the toolbar buttons to **clean up formatting** (remove extra spaces), change text case, or clear the input. A dedicated area shows **spelling/grammar suggestions** (demo) and allows you to **compare two texts** for similarity. - **Results Dashboard**: The right panel updates in real-time. It shows **basic metrics** (word/character count, reading time), **readability scores** from three algorithms (Flesch-Kincaid, SMOG, Coleman-Liau), and a **visual keyword density chart** for the most frequent terms. - **Advanced Analysis**: The tool performs a **sentiment analysis** to classify the tone as positive, negative, or neutral, and lists related emotional words. It also includes a basic **language detection** feature. The **Export report** button downloads a JSON file with all current metrics.

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