fmode-voc-projects/scripts/tools/hongchengdaojia/hongcheng-analyze-xhs.js

#!/usr/bin/env node
/**
 * 洪城到家 · 小红书竞品数据分析脚本
 *
 * 功能：
 *   1. 从 _merged.json 读取数据，按品牌（product）分类
 *   2. 识别本品（洪诚到家）vs 竞品（天鹅到家、好孕妈妈、多喜娃、妈咪无忧等）
 *   3. 计算各品牌的声量、情感、标签、假设覆盖
 *   4. 输出结构化分析报告（控制台 + HTML）
 *
 * 用法：
 *   node scripts/tools/xhs-analyze.js
 *   node scripts/tools/xhs-analyze.js --html
 */

const fs = require('fs');
const path = require('path');

const ROOT = path.resolve(__dirname, '..', '..');
const RAW_DIR = path.join(ROOT, 'docs', '洪城到家', 'raw');
const MERGED_PATH = path.join(RAW_DIR, '_merged.json');
const REPORT_DIR = path.join(ROOT, 'reports');

if (!fs.existsSync(REPORT_DIR)) fs.mkdirSync(REPORT_DIR, { recursive: true });

// =============================================================================
// 品牌映射配置
// =============================================================================

const BRAND_META = {
    '洪诚到家月嫂': {
        label: '洪诚到家',
        type: 'self',
        aliases: ['洪城到家', '洪诚家政', '南昌洪诚'],
    },
    '天鹅到家月嫂': {
        label: '天鹅到家',
        type: 'competitor',
        tier: '全国龙头',
        aliases: ['天鹅到家', '天鹅家政'],
    },
    '好孕妈妈月嫂': {
        label: '好孕妈妈',
        type: 'competitor',
        tier: '全国龙头',
        aliases: ['好孕妈妈', '好孕'],
    },
    '多喜娃月嫂': {
        label: '多喜娃',
        type: 'competitor',
        tier: '区域强者',
        aliases: ['多喜娃'],
    },
    '妈咪无忧月嫂': {
        label: '妈咪无忧',
        type: 'competitor',
        tier: '区域强者',
        aliases: ['妈咪无忧'],
    },
    '宜尔宝月嫂': {
        label: '宜尔宝',
        type: 'competitor',
        tier: '区域',
        aliases: ['宜尔宝'],
    },
    '爱侬家政月嫂': {
        label: '爱侬家政',
        type: 'competitor',
        tier: '区域',
        aliases: ['爱侬家政', '爱侬'],
    },
    '优护佳月嫂': {
        label: '优护佳',
        type: 'competitor',
        tier: '区域',
        aliases: ['优护佳'],
    },
};

const SELF_KEYWORDS = ['洪诚到家', '洪城到家', '洪诚家政', '南昌洪诚'];
const COMPETITOR_KEYWORDS = ['天鹅到家', '好孕妈妈', '多喜娃', '妈咪无忧', '宜尔宝', '爱侬家政', '优护佳'];

// =============================================================================
// 假设（Hypothesis）配置
// =============================================================================

const HYPOTHESIS_META = {
    H1: { label: '医院地推', desc: '医院/产检/待产场景是高效获客渠道' },
    H2: { label: '价格透明', desc: '明码标价是转化关键' },
    H3: { label: '短剧营销', desc: '短剧/视频内容提升品牌认知' },
    H4: { label: '专业度信任', desc: '专业资质证明是信任基础' },
    H5: { label: '社区店威胁', desc: '社区小店是主要竞争对手' },
    H6: { label: '老带新', desc: '口碑推荐是低成本获客渠道' },
    H7: { label: '搜索主力', desc: '美团/小红书是搜索主力平台' },
    H8: { label: '服务保障', desc: '不满意能换是核心保障诉求' },
};

const HYPOTHESIS_KEYWORDS = {
    H1: ['医院', '产检', '待产', '生孩子', '妇幼', '生产', '月嫂怎么找'],
    H2: ['价格', '多少钱', '收费', '报价', '性价比', '便宜', '贵', '月嫂多少钱'],
    H3: ['短剧', '抖音', '视频', '小红书', '看到', '刷到'],
    H4: ['专业', '资质', '证书', '星级', '靠谱', '放心', '正规', '经验'],
    H5: ['社区', '小店', '私人', '对比', '选择', '附近'],
    H6: ['朋友', '推荐', '介绍', '转介绍', '口碑', '好评', '亲戚', '邻居'],
    H7: ['美团', '大众点评', '搜索', '排名', '评价', '小红书', '抖音'],
    H8: ['换', '退', '不满意', '保障', '售后', '风险', '能换', '换人'],
};

// =============================================================================
// 标签规则
// =============================================================================

const TAG_RULES = [
    { tag: '价格敏感', re: /价格|多少钱|贵|便宜|性价比|收费|报价|花销|消费/ },
    { tag: '专业度关注', re: /专业|资质|证书|星级|培训|经验|年限|持证/ },
    { tag: '安全保障', re: /放心|靠谱|安全|保障|正规|放心|靠谱/ },
    { tag: '医院渠道', re: /医院|产检|妇幼|待产|生孩子|建档|临产/ },
    { tag: '熟人推荐', re: /朋友推荐|介绍|口碑|好评|亲戚|邻居|同事|推荐/ },
    { tag: '线上搜索', re: /美团|小红书|抖音|搜索|大众点评|看到|刷到/ },
    { tag: '服务担忧', re: /换|退|不满意|售后|保障|风险|换人|投诉/ },
    { tag: '婆媳关系', re: /婆婆|奶奶|家里|老人|家婆|丈母娘/ },
    { tag: '职场妈妈', re: /上班|工作|复工|职场|产假|回去上班/ },
    { tag: '新手爸妈', re: /新手|第一胎|第一次|头胎|没经验|不懂/ },
    { tag: '决策犹豫', re: /纠结|犹豫|担心|怕|考虑|不知道|怎么选/ },
    { tag: '月嫂面试', re: /面试|挑|选择|对比|比较|筛选/ },
    { tag: '月子餐', re: /月子餐|饮食|营养|煲汤|炖汤|忌口/ },
    { tag: '新生儿护理', re: /新生儿|宝宝|婴儿|黄疸|脐带|喂养|母乳/ },
    { tag: '产后恢复', re: /产后|恢复|身材|盆地肌|腹直肌|月子病/ },
    { tag: '情绪价值', re: /心情|情绪|焦虑|抑郁|崩溃|开心|舒服/ },
];

// =============================================================================
// 情感规则
// =============================================================================

const SENTIMENT_POS = /好|推荐|满意|专业|靠谱|放心|值得|不错|棒|优秀|喜欢|感谢|舒服|贴心|耐心|细心|开心|放心/;
const SENTIMENT_NEG = /差|坑|骗|贵|不专业|不满意|后悔|吐槽|垃圾|失望|糟糕|骗人|黑|投诉|暴力|态度差|不负责任/;
const SENTIMENT_CONFLICT = /但是|可是|纠结|担心|犹豫|想又怕|虽然|不过|可惜/;

function inferSentiment(text) {
    const t = String(text || '');
    const pos = SENTIMENT_POS.test(t);
    const neg = SENTIMENT_NEG.test(t);
    const conf = SENTIMENT_CONFLICT.test(t);
    if (conf && (pos || neg)) return 'conflicted';
    if (pos && !neg) return 'positive';
    if (neg && !pos) return 'negative';
    return 'neutral';
}

function inferTags(text) {
    const tags = [];
    for (const r of TAG_RULES) {
        if (r.re.test(text || '')) tags.push(r.tag);
    }
    return tags;
}

function inferHypotheses(text, extraHypos = []) {
    const results = new Set(extraHypos || []);
    const t = String(text || '').toLowerCase();
    for (const [h, kws] of Object.entries(HYPOTHESIS_KEYWORDS)) {
        for (const kw of kws) {
            if (t.includes(kw.toLowerCase())) { results.add(h); break; }
        }
    }
    return Array.from(results);
}

// =============================================================================
// 数据加载与预处理
// =============================================================================

function loadData() {
    if (!fs.existsSync(MERGED_PATH)) {
        console.error(`❌ 找不到数据文件: ${MERGED_PATH}`);
        console.error('   请先运行: node scripts/tools/hongcheng-collect.js --batch=all --merge');
        process.exit(1);
    }
    const d = JSON.parse(fs.readFileSync(MERGED_PATH, 'utf8'));
    const items = (d.items || []).filter((i) => i.content && i.content.length > 3);
    console.log(`✅ 加载 ${items.length} 条 VOC 数据 (平台: ${Object.keys(d.meta.platforms || {}).join(', ')})`);
    return { items, meta: d.meta };
}

function classifyBrand(product) {
    const p = String(product || '');
    const selfFound = SELF_KEYWORDS.some((k) => p.includes(k));
    if (selfFound) return 'self';
    const compFound = COMPETITOR_KEYWORDS.some((k) => p.includes(k));
    if (compFound) return 'competitor';
    return 'other';
}

function mapBrandLabel(product) {
    const p = String(product || '');
    for (const [kw, meta] of Object.entries(BRAND_META)) {
        if (p.includes(kw)) return meta.label;
        for (const alias of (meta.aliases || [])) {
            if (p.includes(alias)) return meta.label;
        }
    }
    return p;
}

function preprocessItems(items) {
    return items.map((it) => {
        const brandClass = classifyBrand(it.product);
        const brandLabel = mapBrandLabel(it.product);
        const sentiment = inferSentiment(it.content);
        const tags = inferTags(it.content);
        const hypotheses = inferHypotheses(it.content, it.hypothesis || []);
        return { ...it, brandClass, brandLabel, sentiment, tags, hypotheses };
    });
}

// =============================================================================
// 分析函数
// =============================================================================

function analyzeByBrand(items) {
    const brands = {};
    for (const it of items) {
        const b = it.brandLabel;
        if (!brands[b]) {
            brands[b] = {
                label: b,
                class: it.brandClass,
                items: [],
                sentiment: { positive: 0, negative: 0, neutral: 0, conflicted: 0 },
                tags: {},
                hypotheses: {},
                topLiked: [],
                ipDistribution: {},
                typeDistribution: { video: 0, comment: 0 },
            };
        }
        brands[b].items.push(it);
        brands[b].sentiment[it.sentiment] = (brands[b].sentiment[it.sentiment] || 0) + 1;
        brands[b].typeDistribution[it.type] = (brands[b].typeDistribution[it.type] || 0) + 1;
        for (const t of (it.tags || [])) {
            brands[b].tags[t] = (brands[b].tags[t] || 0) + 1;
        }
        for (const h of (it.hypotheses || [])) {
            brands[b].hypotheses[h] = (brands[b].hypotheses[h] || 0) + 1;
        }
        if (it.ip) {
            brands[b].ipDistribution[it.ip] = (brands[b].ipDistribution[it.ip] || 0) + 1;
        }
    }
    for (const b of Object.values(brands)) {
        b.topLiked = [...b.items].sort((a, c) => (c.likes || 0) - (a.likes || 0)).slice(0, 5);
    }
    return brands;
}

function analyzeHypothesisCoverage(items) {
    const coverage = {};
    for (const h of Object.keys(HYPOTHESIS_META)) {
        coverage[h] = { meta: HYPOTHESIS_META[h], count: 0, examples: [], byBrand: {} };
    }
    for (const it of items) {
        for (const h of (it.hypotheses || [])) {
            if (coverage[h]) {
                coverage[h].count++;
                if (coverage[h].examples.length < 3) {
                    coverage[h].examples.push({ content: it.content.slice(0, 200), likes: it.likes, platform: it.platform, brand: it.brandLabel });
                }
                coverage[h].byBrand[it.brandLabel] = (coverage[h].byBrand[it.brandLabel] || 0) + 1;
            }
        }
    }
    return coverage;
}

function analyzeTags(items) {
    const tagStats = {};
    for (const it of items) {
        for (const t of (it.tags || [])) {
            if (!tagStats[t]) tagStats[t] = { count: 0, examples: [], byBrand: {} };
            tagStats[t].count++;
            if (tagStats[t].examples.length < 2) {
                tagStats[t].examples.push({ content: it.content.slice(0, 150), likes: it.likes, platform: it.platform });
            }
            tagStats[t].byBrand[it.brandLabel] = (tagStats[t].byBrand[it.brandLabel] || 0) + 1;
        }
    }
    return tagStats;
}

function analyzePainPoints(items) {
    const painPatterns = {
        '价格太贵': { re: /贵|价格高|太贵|付不起|花钱|费用/ },
        '不专业': { re: /不专业|没经验|不靠谱|证书|资质/ },
        '服务不满意': { re: /不满意|换|退|投诉|差|坑/ },
        '找不到合适的': { re: /找不到|不知道怎么选|纠结|犹豫|怕|担心/ },
        '家人反对': { re: /婆婆不让|家里不同意|老人不让|老公说/ },
        '信息不透明': { re: /不了解|不知道|不清楚|怎么找/ },
    };
    const pains = {};
    for (const [name, cfg] of Object.entries(painPatterns)) {
        pains[name] = { count: 0, examples: [], byBrand: {} };
    }
    for (const it of items) {
        for (const [name, cfg] of Object.entries(painPatterns)) {
            if (cfg.re.test(it.content)) {
                pains[name].count++;
                if (pains[name].examples.length < 3) {
                    pains[name].examples.push({ content: it.content.slice(0, 180), likes: it.likes, platform: it.platform, brand: it.brandLabel });
                }
                pains[name].byBrand[it.brandLabel] = (pains[name].byBrand[it.brandLabel] || 0) + 1;
            }
        }
    }
    return pains;
}

function analyzeIpGeo(items) {
    const geo = {};
    for (const it of items) {
        if (it.ip) {
            if (!geo[it.ip]) geo[it.ip] = { count: 0, brands: {} };
            geo[it.ip].count++;
            geo[it.ip].brands[it.brandLabel] = (geo[it.ip].brands[it.brandLabel] || 0) + 1;
        }
    }
    return geo;
}

function analyzeSelfVsCompetitor(items) {
    const self = items.filter((i) => i.brandClass === 'self');
    const competitors = items.filter((i) => i.brandClass === 'competitor');
    const other = items.filter((i) => i.brandClass === 'other');
    const brands = analyzeByBrand(items);

    const selfSentiment = { positive: 0, negative: 0, neutral: 0, conflicted: 0 };
    for (const it of self) selfSentiment[it.sentiment] = (selfSentiment[it.sentiment] || 0) + 1;

    const compSentiment = { positive: 0, negative: 0, neutral: 0, conflicted: 0 };
    for (const it of competitors) compSentiment[it.sentiment] = (compSentiment[it.sentiment] || 0) + 1;

    const tagDiff = {};
    const selfTags = {};
    const compTags = {};
    for (const it of self) { for (const t of (it.tags || [])) selfTags[t] = (selfTags[t] || 0) + 1; }
    for (const it of competitors) { for (const t of (it.tags || [])) compTags[t] = (compTags[t] || 0) + 1; }
    const allTags = new Set([...Object.keys(selfTags), ...Object.keys(compTags)]);
    for (const t of allTags) {
        const s = selfTags[t] || 0;
        const c = compTags[t] || 0;
        tagDiff[t] = { self: s, competitor: c, delta: s - c };
    }

    const selfTopTags = Object.entries(selfTags).sort((a, b) => b[1] - a[1]).slice(0, 5);
    const compTopTags = Object.entries(compTags).sort((a, b) => b[1] - a[1]).slice(0, 5);

    return { self, competitors, other, brands, selfSentiment, compSentiment, tagDiff, selfTopTags, compTopTags };
}

function analyzeDecisionJourney(items) {
    const stages = {
        '需求触发': { re: /怀孕了|待产|产检|建档|新手爸妈|第一胎|头胎/, count: 0, examples: [] },
        '信息搜索': { re: /怎么找|哪家好|多少钱|推荐|搜索|小红书|抖音|美团|大众点评/, count: 0, examples: [] },
        '决策比较': { re: /纠结|犹豫|对比|比较|面试|选择|挑|天鹅到家|好孕妈妈|多喜娃/, count: 0, examples: [] },
        '购买/签约': { re: /签了|定了|请了|下单|付款|签约/, count: 0, examples: [] },
        '服务体验': { re: /用了|服务|月嫂|照顾|宝宝|做饭|护理|月子/, count: 0, examples: [] },
        '口碑传播': { re: /推荐|介绍|朋友|转介绍|好评|吐槽|分享|发小红书/, count: 0, examples: [] },
    };
    for (const it of items) {
        for (const [stage, cfg] of Object.entries(stages)) {
            if (cfg.re.test(it.content)) {
                cfg.count++;
                if (cfg.examples.length < 3) {
                    cfg.examples.push({ content: it.content.slice(0, 160), likes: it.likes, platform: it.platform, brand: it.brandLabel });
                }
            }
        }
    }
    return stages;
}

// =============================================================================
// 控制台报告输出
// =============================================================================

function pad(s, len = 24) { return String(s).padEnd(len); }
function bar(n, total, w = 20) {
    if (!total) return '░'.repeat(w);
    const f = Math.round((n / total) * w);
    return '█'.repeat(f) + '░'.repeat(w - f);
}

function printSection(title) {
    console.log('\n' + '═'.repeat(72));
    console.log('  ' + title);
    console.log('═'.repeat(72));
}

function printReport(analysis) {
    const { items, brands, hypoCov, tagStats, painPoints, geo, selfVsComp, journey, meta } = analysis;
    const total = items.length;

    console.log('\n');
    console.log('╔══════════════════════════════════════════════════════════════════╗');
    console.log('║      洪城到家 · 小红书 VOC 竞品分析报告                           ║');
    console.log('╚══════════════════════════════════════════════════════════════════╝');

    // 1. 总览
    printSection('一、数据总览');
    const selfTotal = selfVsComp.self.length;
    const compTotal = selfVsComp.competitors.length;
    const otherTotal = selfVsComp.other.length;
    console.log(`  总 VOC 条数：${total}`);
    console.log(`  本品（洪诚到家）：${selfTotal} 条 (${total ? ((selfTotal/total)*100).toFixed(1) : 0}%)`);
    console.log(`  竞品讨论：${compTotal} 条 (${total ? ((compTotal/total)*100).toFixed(1) : 0}%)`);
    console.log(`  其他话题：${otherTotal} 条 (${total ? ((otherTotal/total)*100).toFixed(1) : 0}%)`);
    console.log(`  品牌覆盖：${Object.keys(brands).length} 个`);
    console.log(`  数据采集时间：${(meta.collectedAt || '').slice(0, 10)}`);

    // 2. 声量排行
    printSection('二、品牌声量排行');
    const brandList = Object.entries(brands).sort((a, b) => b[1].items.length - a[1].items.length);
    const brandTotal = brandList.reduce((s, [, b]) => s + b.items.length, 0);
    console.log(`  ${pad('品牌')}  ${pad('类型')}    ${pad('声量')}  占比      情感分布`);
    console.log('  ' + '─'.repeat(68));
    for (const [label, b] of brandList) {
        const cnt = b.items.length;
        const pct = brandTotal ? ((cnt / brandTotal) * 100).toFixed(1) : '0.0';
        const p = b.sentiment.positive || 0;
        const n = b.sentiment.negative || 0;
        const cls = b.class === 'self' ? '本品' : (BRAND_META[label]?.tier || '竞品');
        console.log(`  ${pad(label, 10)} ${pad(cls, 8)} ${pad(cnt, 6)} ${pct.padStart(6)}%  ${bar(p + n, cnt, 8)} +${p}/-${n}`);
    }

    // 3. 本品 vs 竞品情感对比
    printSection('三、本品 vs 竞品 情感分布');
    const ss = selfVsComp.selfSentiment;
    const cs = selfVsComp.compSentiment;
    const sTotal = selfTotal || 1;
    const cTotal = compTotal || 1;
    console.log(`  ${pad('情感')}${pad('本品('+selfTotal+')',14)}${pad('竞品('+compTotal+')',14)}差异`);
    console.log('  ' + '─'.repeat(60));
    for (const sent of ['positive', 'negative', 'neutral', 'conflicted']) {
        const sl = ss[sent] || 0;
        const cl = cs[sent] || 0;
        const sd = sTotal ? ((sl / sTotal) * 100).toFixed(0) : 0;
        const cd = cTotal ? ((cl / cTotal) * 100).toFixed(0) : 0;
        const diff = parseInt(sd) - parseInt(cd);
        const sign = diff > 0 ? '+' : '';
        const labels = { positive: '正向', negative: '负向', neutral: '中立', conflicted: '矛盾' };
        console.log(`  ${pad(labels[sent])}${pad(sl + '(' + sd + '%)', 14)}${pad(cl + '(' + cd + '%)', 14)}${sign}${diff}%`);
    }

    // 4. 标签分布
    printSection('四、用户关注标签分布 (TOP 15)');
    const sortedTags = Object.entries(tagStats).sort((a, b) => b[1].count - a[1].count).slice(0, 15);
    console.log(`  ${pad('标签')}  ${pad('出现次数')}  品牌分布`);
    console.log('  ' + '─'.repeat(65));
    for (const [tag, s] of sortedTags) {
        const topBrands = Object.entries(s.byBrand).sort((a, b) => b[1] - a[1]).slice(0, 3)
            .map(([b, c]) => `${b}(${c})`).join(' ');
        console.log(`  ${pad(tag, 12)} ${pad(s.count, 8)} ${topBrands}`);
    }

    // 5. 假设验证
    printSection('五、假设（Hypothesis）验证覆盖');
    const sortedHypos = Object.entries(hypoCov).sort((a, b) => b[1].count - a[1].count);
    console.log(`  ${pad('假设')}  ${pad('描述')}              ${pad('声量')}  验证状态`);
    console.log('  ' + '─'.repeat(68));
    for (const [h, data] of sortedHypos) {
        const m = HYPOTHESIS_META[h];
        const status = data.count >= 100 ? '✅ 充分' : data.count >= 30 ? '⚠️  少量' : '❌ 稀缺';
        console.log(`  ${pad(h + ' ' + m.label, 16)} ${pad(data.count, 8)} ${status}`);
    }

    // 6. 痛点分析
    printSection('六、核心痛点分析');
    const sortedPains = Object.entries(painPoints).sort((a, b) => b[1].count - a[1].count);
    console.log(`  ${pad('痛点类型')}  ${pad('出现次数')}  品牌分布`);
    console.log('  ' + '─'.repeat(65));
    for (const [name, p] of sortedPains) {
        if (p.count === 0) continue;
        const topBrands = Object.entries(p.byBrand).sort((a, b) => b[1] - a[1]).slice(0, 3)
            .map(([b, c]) => `${b}(${c})`).join(' ');
        console.log(`  ${pad(name, 14)} ${pad(p.count, 8)} ${topBrands}`);
    }

    // 7. IP地理
    printSection('七、IP 地理分布 (TOP 10)');
    const sortedGeo = Object.entries(geo).sort((a, b) => b[1].count - a[1].count).slice(0, 10);
    console.log(`  ${pad('IP属地')}  ${pad('条数')}  品牌占比`);
    console.log('  ' + '─'.repeat(60));
    for (const [ip, g] of sortedGeo) {
        const topBrand = Object.entries(g.brands).sort((a, b) => b[1] - a[1])[0];
        const pct = g.total ? ((topBrand[1] / g.count) * 100).toFixed(0) : 0;
        console.log(`  ${pad(ip, 12)} ${pad(g.count, 6)} ${topBrand[0]}(${pct}%)`);
    }

    // 8. 决策旅程
    printSection('八、用户决策旅程分布');
    const journeyTotal = Object.values(journey).reduce((s, c) => s + c.count, 0);
    for (const [stage, cfg] of Object.entries(journey)) {
        const pct = journeyTotal ? ((cfg.count / journeyTotal) * 100).toFixed(1) : '0.0';
        console.log(`  ${pad(stage, 14)} ${pad(cfg.count, 6)} ${pct}%  ${bar(cfg.count, journeyTotal, 20)}`);
    }

    // 9. 高赞 VOC
    printSection('九、高赞 VOC 精选 (TOP 15)');
    const topLiked = [...items].sort((a, b) => (b.likes || 0) - (a.likes || 0)).slice(0, 15);
    for (const it of topLiked) {
        const content = String(it.content).slice(0, 80);
        console.log(`  [${pad(it.platform, 7)}] ♥${String(it.likes || 0).padStart(5)} [${pad(it.brandLabel, 8)}] ${content}`);
    }

    // 10. 本品声量TOP标签 vs 竞品
    printSection('十、本品 vs 竞品 标签差异分析');
    const tagDiffSorted = Object.entries(selfVsComp.tagDiff).sort((a, b) => Math.abs(b[1].delta) - Math.abs(a[1].delta));
    console.log(`  ${pad('标签')}   本品  竞品   差值   机会`);
    console.log('  ' + '─'.repeat(60));
    for (const [tag, d] of tagDiffSorted.slice(0, 10)) {
        const opportunity = d.self < d.competitor ? '⬆️ 本品机会' : '⬇️ 竞品领先';
        console.log(`  ${pad(tag, 10)} ${pad(d.self, 5)} ${pad(d.competitor, 5)} ${pad(d.delta > 0 ? '+' + d.delta : d.delta, 6)} ${opportunity}`);
    }

    console.log('\n' + '═'.repeat(72));
}

// =============================================================================
// HTML 报告生成
// =============================================================================

function generateHTML(analysis) {
    const { items, brands, hypoCov, tagStats, painPoints, geo, selfVsComp, journey, meta } = analysis;
    const total = items.length;

    const brandList = Object.entries(brands).sort((a, b) => b[1].items.length - a[1].items.length);
    const sortedTags = Object.entries(tagStats).sort((a, b) => b[1].count - a[1].count).slice(0, 15);
    const sortedHypos = Object.entries(hypoCov).sort((a, b) => b[1].count - a[1].count);
    const sortedPains = Object.entries(painPoints).sort((a, b) => b[1].count - a[1].count);
    const sortedGeo = Object.entries(geo).sort((a, b) => b[1].count - a[1].count).slice(0, 10);
    const topLiked = [...items].sort((a, b) => (b.likes || 0) - (a.likes || 0)).slice(0, 20);
    const journeyTotal = Object.values(journey).reduce((s, c) => s + c.count, 0);

    const brandRows = brandList.map(([label, b]) => {
        const cnt = b.items.length;
        const pct = total ? ((cnt / total) * 100).toFixed(1) : '0.0';
        const cls = b.class === 'self' ? 'tag-self' : 'tag-comp';
        const clsLabel = b.class === 'self' ? '本品' : (BRAND_META[label]?.tier || '竞品');
        return `<tr>
            <td><span class="brand-tag ${cls}">${label}</span></td>
            <td>${clsLabel}</td>
            <td class="num">${cnt}</td>
            <td class="num">${pct}%</td>
            <td class="num positive">${b.sentiment.positive || 0}</td>
            <td class="num negative">${b.sentiment.negative || 0}</td>
            <td class="num">${b.sentiment.neutral || 0}</td>
            <td class="num">${b.sentiment.conflicted || 0}</td>
        </tr>`;
    }).join('\n');

    const tagRows = sortedTags.map(([tag, s]) => {
        const brands = Object.entries(s.byBrand).sort((a, b) => b[1] - a[1]).slice(0, 3)
            .map(([b, c]) => `<span class="mini-tag">${b} ${c}</span>`).join(' ');
        return `<tr><td>${tag}</td><td class="num">${s.count}</td><td>${brands}</td></tr>`;
    }).join('\n');

    const hypoRows = sortedHypos.map(([h, data]) => {
        const m = HYPOTHESIS_META[h];
        const status = data.count >= 100 ? '✅ 充分' : data.count >= 30 ? '⚠️ 少量' : '❌ 稀缺';
        const barW = Math.min(100, (data.count / 200) * 100);
        return `<tr>
            <td><strong>${h}</strong><br><small>${m.label}</small></td>
            <td><small>${m.desc}</small></td>
            <td class="num">${data.count}</td>
            <td><div class="mini-bar"><div class="mini-fill" style="width:${barW}%"></div></div></td>
            <td>${status}</td>
        </tr>`;
    }).join('\n');

    const painRows = sortedPains.filter(([,p]) => p.count > 0).map(([name, p]) => {
        const brands = Object.entries(p.byBrand).sort((a, b) => b[1] - a[1]).slice(0, 3)
            .map(([b, c]) => `<span class="mini-tag">${b} ${c}</span>`).join(' ');
        return `<tr><td>${name}</td><td class="num">${p.count}</td><td>${brands}</td></tr>`;
    }).join('\n');

    const geoRows = sortedGeo.map(([ip, g]) => {
        const topBrand = Object.entries(g.brands).sort((a, b) => b[1] - a[1])[0];
        return `<tr><td>${ip}</td><td class="num">${g.count}</td><td>${topBrand[0]} (${topBrand[1]})</td></tr>`;
    }).join('\n');

    const journeyRows = Object.entries(journey).map(([stage, cfg]) => {
        const pct = journeyTotal ? ((cfg.count / journeyTotal) * 100).toFixed(1) : '0.0';
        const barW = journeyTotal ? ((cfg.count / journeyTotal) * 100) : 0;
        return `<tr>
            <td>${stage}</td>
            <td class="num">${cfg.count}</td>
            <td class="num">${pct}%</td>
            <td><div class="mini-bar"><div class="mini-fill" style="width:${barW}%"></div></div></td>
        </tr>`;
    }).join('\n');

    const vocRows = topLiked.map((it) => {
        const content = String(it.content).replace(/</g, '&lt;').replace(/>/g, '&gt;').slice(0, 120);
        const ex = it.content.length > 120 ? '...' : '';
        return `<tr>
            <td class="num">♥ ${it.likes || 0}</td>
            <td>${it.platform}</td>
            <td><span class="brand-tag ${it.brandClass === 'self' ? 'tag-self' : 'tag-comp'}">${it.brandLabel}</span></td>
            <td><small>${content}${ex}</small></td>
        </tr>`;
    }).join('\n');

    const selfSent = selfVsComp.selfSentiment;
    const compSent = selfVsComp.compSentiment;
    const sentimentData = JSON.stringify({ self: selfSent, competitor: compSent });

    return `<!DOCTYPE html>
<html lang="zh-CN">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>洪城到家 · 小红书竞品VOC分析报告</title>
<style>
:root {
    --bg-0: #ffffff; --bg-1: #f7f8fa; --bg-2: #eef0f4; --border: #e2e5ed;
    --text-1: #1a1d23; --text-2: #4a5568; --text-3: #8896a6;
    --accent: #2563eb; --accent-light: #dbeafe;
    --positive: #16a34a; --negative: #dc2626; --neutral: #6b7280;
    --tag-self-bg: #dbeafe; --tag-self-color: #1e40af;
    --tag-comp-bg: #fce7f3; --tag-comp-color: #9d174d;
    --radius: 8px;
}
*, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }
body { font-family: 'PingFang SC', 'Microsoft YaHei', 'Inter', sans-serif; background: var(--bg-1); color: var(--text-1); font-size: 14px; line-height: 1.6; }
.container { max-width: 1200px; margin: 0 auto; padding: 32px 20px; }

.hd { background: linear-gradient(135deg, #1e3a5f 0%, #2563eb 100%); color: white; padding: 40px 32px; border-radius: var(--radius); margin-bottom: 32px; }
.hd h1 { font-size: 1.8rem; font-weight: 800; margin-bottom: 8px; }
.hd p { opacity: 0.85; font-size: 0.9rem; }
.hd .meta { margin-top: 16px; display: flex; gap: 24px; font-size: 0.82rem; opacity: 0.8; }

.kpi-row { display: grid; grid-template-columns: repeat(4, 1fr); gap: 16px; margin-bottom: 32px; }
.kpi { background: white; border-radius: var(--radius); padding: 20px; border: 1px solid var(--border); }
.kpi .val { font-size: 2rem; font-weight: 800; color: var(--accent); }
.kpi .lbl { color: var(--text-2); font-size: 0.8rem; margin-top: 4px; }
.kpi.self-card .val { color: #1e40af; }

.card { background: white; border-radius: var(--radius); border: 1px solid var(--border); margin-bottom: 24px; overflow: hidden; }
.card-head { padding: 16px 24px; border-bottom: 1px solid var(--border); font-weight: 700; font-size: 1rem; background: var(--bg-1); }
.card-body { padding: 20px 24px; }

table { width: 100%; border-collapse: collapse; }
th { text-align: left; padding: 10px 12px; font-size: 0.78rem; color: var(--text-2); text-transform: uppercase; letter-spacing: 0.05em; border-bottom: 2px solid var(--border); background: var(--bg-1); }
td { padding: 10px 12px; border-bottom: 1px solid var(--bg-2); vertical-align: top; }
tr:last-child td { border-bottom: none; }
tr:hover td { background: var(--bg-1); }
.num { text-align: right; font-variant-numeric: tabular-nums; }
.positive { color: var(--positive); font-weight: 600; }
.negative { color: var(--negative); font-weight: 600; }

.brand-tag { display: inline-block; padding: 2px 8px; border-radius: 4px; font-size: 0.78rem; font-weight: 600; }
.tag-self { background: var(--tag-self-bg); color: var(--tag-self-color); }
.tag-comp { background: var(--tag-comp-bg); color: var(--tag-comp-color); }

.mini-tag { display: inline-block; background: var(--bg-2); padding: 1px 6px; border-radius: 3px; font-size: 0.72rem; margin: 1px; }
.mini-bar { background: var(--bg-2); border-radius: 3px; height: 8px; overflow: hidden; }
.mini-fill { background: var(--accent); height: 100%; border-radius: 3px; transition: width 0.3s; }

.chart-grid { display: grid; grid-template-columns: 1fr 1fr; gap: 24px; }
.sentiment-chart { display: flex; flex-direction: column; gap: 12px; }
.sent-row { display: flex; align-items: center; gap: 12px; }
.sent-label { width: 60px; font-size: 0.82rem; color: var(--text-2); }
.sent-bar-bg { flex: 1; height: 20px; background: var(--bg-2); border-radius: 4px; overflow: hidden; }
.sent-fill { height: 100%; border-radius: 4px; }
.sent-fill.pos { background: var(--positive); }
.sent-fill.neg { background: var(--negative); }
.sent-fill.neu { background: var(--neutral); }
.sent-fill.con { background: #f59e0b; }
.sent-count { width: 50px; text-align: right; font-size: 0.82rem; font-variant-numeric: tabular-nums; }

.example { background: var(--bg-1); border-radius: 6px; padding: 12px; margin-top: 8px; font-size: 0.82rem; color: var(--text-2); border-left: 3px solid var(--accent); }
.example small { color: var(--text-3); }

.footer { text-align: center; padding: 32px; color: var(--text-3); font-size: 0.78rem; }

@media (max-width: 768px) {
    .kpi-row { grid-template-columns: repeat(2, 1fr); }
    .chart-grid { grid-template-columns: 1fr; }
}
</style>
</head>
<body>
<div class="container">

<div class="hd">
    <h1>洪城到家 · 小红书竞品VOC分析报告</h1>
    <p>基于真实用户评论数据的多维度竞品分析 | 声量 × 情感 × 痛点 × 假设验证</p>
    <div class="meta">
        <span>📊 总 VOC: ${total} 条</span>
        <span>🏷️ 品牌覆盖: ${brandList.length} 个</span>
        <span>📅 采集时间: ${(meta.collectedAt || '').slice(0, 10)}</span>
    </div>
</div>

<div class="kpi-row">
    <div class="kpi self-card">
        <div class="val">${selfVsComp.self.length}</div>
        <div class="lbl">本品声量 (洪诚到家)</div>
    </div>
    <div class="kpi">
        <div class="val">${selfVsComp.competitors.length}</div>
        <div class="lbl">竞品声量合计</div>
    </div>
    <div class="kpi">
        <div class="val">${brandList.filter(([,b]) => b.class === 'competitor').length}</div>
        <div class="lbl">竞品种类</div>
    </div>
    <div class="kpi">
        <div class="val">${(selfVsComp.self.length && total) ? ((selfVsComp.self.length/total)*100).toFixed(1)+'%' : '0%'}</div>
        <div class="lbl">本品占比</div>
    </div>
</div>

<div class="card">
    <div class="card-head">一、品牌声量排行</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr>
                <th>品牌</th><th>类型</th><th class="num">声量</th><th class="num">占比</th>
                <th class="num positive">正向</th><th class="num negative">负向</th>
                <th class="num">中立</th><th class="num">矛盾</th>
            </tr></thead>
            <tbody>${brandRows}</tbody>
        </table>
    </div>
</div>

<div class="card">
    <div class="card-head">二、本品 vs 竞品 情感分布对比</div>
    <div class="card-body">
        <div class="chart-grid">
            <div>
                <h4 style="margin-bottom:12px;color:var(--text-2);font-size:0.85rem">本品（洪诚到家）情感</h4>
                <div class="sentiment-chart">
                    ${['positive','negative','neutral','conflicted'].map(s => {
                        const labels = {positive:'正向',negative:'负向',neutral:'中立',conflicted:'矛盾'};
                        const colors = {positive:'pos',negative:'neg',neutral:'neu',conflicted:'con'};
                        const cnt = selfSent[s] || 0;
                        const total2 = selfVsComp.self.length || 1;
                        const w = (cnt/total2)*100;
                        return `<div class="sent-row">
                            <div class="sent-label">${labels[s]}</div>
                            <div class="sent-bar-bg"><div class="sent-fill ${colors[s]}" style="width:${w}%"></div></div>
                            <div class="sent-count">${cnt} (${w.toFixed(0)}%)</div>
                        </div>`;
                    }).join('')}
                </div>
            </div>
            <div>
                <h4 style="margin-bottom:12px;color:var(--text-2);font-size:0.85rem">竞品（行业平均）情感</h4>
                <div class="sentiment-chart">
                    ${['positive','negative','neutral','conflicted'].map(s => {
                        const labels = {positive:'正向',negative:'负向',neutral:'中立',conflicted:'矛盾'};
                        const colors = {positive:'pos',negative:'neg',neutral:'neu',conflicted:'con'};
                        const cnt = compSent[s] || 0;
                        const total2 = selfVsComp.competitors.length || 1;
                        const w = (cnt/total2)*100;
                        return `<div class="sent-row">
                            <div class="sent-label">${labels[s]}</div>
                            <div class="sent-bar-bg"><div class="sent-fill ${colors[s]}" style="width:${w}%"></div></div>
                            <div class="sent-count">${cnt} (${w.toFixed(0)}%)</div>
                        </div>`;
                    }).join('')}
                </div>
            </div>
        </div>
    </div>
</div>

<div class="card">
    <div class="card-head">三、用户关注标签分布 (TOP 15)</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr><th>标签</th><th class="num">出现次数</th><th>品牌分布</th></tr></thead>
            <tbody>${tagRows}</tbody>
        </table>
    </div>
</div>

<div class="card">
    <div class="card-head">四、假设（Hypothesis）验证覆盖</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr><th>假设</th><th>描述</th><th class="num">声量</th><th>覆盖进度</th><th>状态</th></tr></thead>
            <tbody>${hypoRows}</tbody>
        </table>
    </div>
</div>

<div class="card">
    <div class="card-head">五、核心痛点分析</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr><th>痛点类型</th><th class="num">出现次数</th><th>品牌分布</th></tr></thead>
            <tbody>${painRows}</tbody>
        </table>
    </div>
</div>

<div class="card">
    <div class="card-head">六、IP 地理分布 (TOP 10)</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr><th>IP属地</th><th class="num">条数</th><th>主要品牌</th></tr></thead>
            <tbody>${geoRows}</tbody>
        </table>
    </div>
</div>

<div class="card">
    <div class="card-head">七、用户决策旅程分布</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr><th>阶段</th><th class="num">出现次数</th><th class="num">占比</th><th>分布</th></tr></thead>
            <tbody>${journeyRows}</tbody>
        </table>
    </div>
</div>

<div class="card">
    <div class="card-head">八、高赞 VOC 精选 (TOP 20)</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr><th>点赞</th><th>平台</th><th>品牌</th><th>内容摘要</th></tr></thead>
            <tbody>${vocRows}</tbody>
        </table>
    </div>
</div>

<div class="card">
    <div class="card-head">九、本品 vs 竞品 标签差异分析</div>
    <div class="card-body" style="overflow-x:auto">
        <table>
            <thead><tr><th>标签</th><th class="num">本品</th><th class="num">竞品</th><th class="num">差值</th><th>洞察</th></tr></thead>
            <tbody>${Object.entries(selfVsComp.tagDiff)
                .sort((a, b) => Math.abs(b[1].delta) - Math.abs(a[1].delta))
                .slice(0, 10).map(([tag, d]) => {
                    const insight = d.self > d.competitor ? '⬆️ 本品关注更多' : '⬇️ 竞品关注更多';
                    return `<tr>
                        <td>${tag}</td>
                        <td class="num">${d.self}</td>
                        <td class="num">${d.competitor}</td>
                        <td class="num ${d.delta > 0 ? 'positive' : 'negative'}">${d.delta > 0 ? '+' : ''}${d.delta}</td>
                        <td><small>${insight}</small></td>
                    </tr>`;
                }).join('\n')}</tbody>
        </table>
    </div>
</div>

<div class="footer">
    <p>洪城到家 · 小红书竞品VOC分析报告 | 数据来源: _merged.json | 生成时间: ${new Date().toLocaleString('zh-CN')}</p>
</div>

</div>
</body>
</html>`;
}

// =============================================================================
// 主函数
// =============================================================================

function main() {
    const argv = process.argv.slice(2);
    const doHTML = argv.includes('--html') || argv.includes('--report');
    const doCompact = argv.includes('--compact');

    console.log('🔍 加载数据...');
    const { items, meta } = loadData();

    console.log('🔧 预处理数据（情感分析、标签、假设）...');
    const processed = preprocessItems(items);

    console.log('📊 执行多维度分析...');
    const brands = analyzeByBrand(processed);
    const hypoCov = analyzeHypothesisCoverage(processed);
    const tagStats = analyzeTags(processed);
    const painPoints = analyzePainPoints(processed);
    const geo = analyzeIpGeo(processed);
    const selfVsComp = analyzeSelfVsCompetitor(processed);
    const journey = analyzeDecisionJourney(processed);

    const analysis = { items: processed, brands, hypoCov, tagStats, painPoints, geo, selfVsComp, journey, meta };

    console.log('📝 生成报告...');
    printReport(analysis);

    if (doHTML) {
        const html = generateHTML(analysis);
        const outPath = path.join(REPORT_DIR, 'xhs-competitor-analysis.html');
        fs.writeFileSync(outPath, html, 'utf8');
        console.log(`\n✅ HTML 报告已生成: ${outPath}`);
    }

    if (!doHTML && !doCompact) {
        console.log('\n💡 提示：使用 --html 参数可生成完整 HTML 报告');
        console.log('    使用 --compact 参数仅显示精简摘要');
    }
}

if (require.main === module) {
    main();
}

module.exports = { loadData, preprocessItems, analyzeByBrand, analyzeHypothesisCoverage, analyzeTags, analyzePainPoints, analyzeIpGeo, analyzeSelfVsCompetitor, analyzeDecisionJourney };