/* Discussion Intelligence — hidden editor-only page.
Sibling of editor-notes.jsx, but instead of editorial commentary scored by
a rubric, this page surfaces *what the cohort is actually discussing* this
week — extracted by the LLM classifier per tweet and aggregated by
scripts/discussionDigest.ts into public/data/xai-discussion-7d.json. */
var DISCUSSION_JSON_URL = '/data/xai-discussion-7d.json';
/* Content-language helper for this page's leaf labels. Reads the global set by
the shared LangToggle; safe because a lang change re-renders DiscussionPage
(it calls useContentLang), which cascades to every child below. */
function _dzh() { return (typeof window !== 'undefined' && window.__contentLang === 'zh'); }
function DiscussionPage() {
var lang = useContentLang();
var zh = lang === 'zh';
var [data, setData] = React.useState(null);
var [err, setErr] = React.useState(null);
React.useEffect(function () {
fetch(DISCUSSION_JSON_URL)
.then(function (r) { return r.ok ? r.json() : Promise.reject(new Error('GET /data/xai-discussion-7d.json → HTTP ' + r.status)); })
.then(setData)
.catch(function (e) { setErr(String(e.message || e)); });
}, []);
if (err) {
return (
{zh ? '討論' : 'Discussion'}
{err}
{zh
? <>討論頁讀取 public/data/xai-discussion-7d.json，由 pnpm discussion-digest 產生。請在 pnpm classify 已把 mood / competitor / dimension 欄位寫進 tweets 表後跑一次。
: <>The Discussion page reads public/data/xai-discussion-7d.json, written by pnpm discussion-digest. Run that once after pnpm classify has populated mood / competitor / dimension fields on the tweets table.}
{zh
? <>這群人實際上在吵什麼、想要什麼、稱讚什麼、抱怨什麼？每個區塊都由逐則推文的訊號擷取（情緒 / 競品 / 開放詞彙面向）驅動，再由 LLM 從彙整數據（而非原始推文）寫成一句話的說明——所以每個文字主張都能追回一個你能重新查詢的數字。
: <>What is this group actually arguing about, wishing for, praising, complaining about? Each section is driven by per-tweet signal extraction (mood / competitor / open-vocab dimension) and a 1-sentence LLM caption written from the aggregates — never from raw tweets — so every prose claim traces back to a number you can re-query.}
);
}
/* ── Generic section shell ── */
function DiscussionSection({ title, sub, caption, children }) {
return (
{title}
{sub}
{caption && (
{caption}
)}
{children}
);
}
/* ── Hot dimensions ── */
function HotDimensionsList({ items }) {
var [expanded, setExpanded] = React.useState({});
if (items.length === 0) {
return
;
}
var max = items[0] && items[0].count ? items[0].count : 1;
function toggle(key) { setExpanded(function (p) { var n = Object.assign({}, p); n[key] = !n[key]; return n; }); }
return (
{items.slice(0, 16).map(function (d) {
var key = d.topic + ':' + d.dimension;
var pct = (d.count / max) * 100;
var isOpen = !!expanded[key];
var sources = d.sources || [];
return (
{isOpen && }
);
})}
);
}
/* ── Reusable: expanded source-tweet list (used by Hot dimensions + Comp map) ── */
function SourceList({ sources }) {
if (!sources || sources.length === 0) {
return
{_dzh() ? '此分類沒有擷取到來源推文。' : 'No source tweets captured for this bucket.'}
;
}
var moodColor = { praise: 'var(--accent)', complaint: 'var(--rose)', wish: 'rgba(249,115,22,0.6)', debate: 'var(--blue)', neutral: 'var(--text-tertiary)' };
function displayText(s) {
var t = s.text || '';
// Best-effort strip of "RT @whoever: " prefix when the root content is shown under its real author.
if (/^RT\s+@/i.test(t)) {
t = t.replace(/^RT\s+@[^:\s]+:\s*/i, '');
}
return t;
}
// Legacy safety net: the committed JSON snapshots still contain the old per-tweet sources
// (many near-identical RT cards). Group them here by cleaned text so the UI already looks
// good on historical data. New digests (with upstream collapseSources) produce distinct
// entries so this is mostly a no-op.
function collapseLegacySources(srcs) {
if (!srcs || srcs.length <= 1) return srcs || [];
var groups = {};
for (var i = 0; i < srcs.length; i++) {
var s = srcs[i];
var t = (s.text || '').replace(/^RT\s+@[^:\s]+:\s*/i, '').trim().toLowerCase();
var key = t.slice(0, 160); // stable enough for these short excerpts
if (!groups[key]) {
groups[key] = { rep: s, handles: [] };
}
groups[key].handles.push(s.handle);
if ((s.views || 0) > (groups[key].rep.views || 0)) {
groups[key].rep = s;
}
}
var out = [];
var keys = Object.keys(groups);
for (var k = 0; k < keys.length; k++) {
var g = groups[keys[k]];
var r = g.rep;
var unique = [];
var seen = {};
for (var h = 0; h < g.handles.length; h++) {
var hh = g.handles[h];
if (!seen[hh]) { seen[hh] = true; unique.push(hh); }
}
var ampN = (r.ampCount != null ? r.ampCount : (r.amplifiers ? r.amplifiers.length : 0));
if (ampN < 2 && unique.length > 1) {
// synthesize for legacy data
r = Object.assign({}, r, { amplifiers: unique, ampCount: unique.length });
}
out.push(r);
}
out.sort(function (a, b) { return (b.views || 0) - (a.views || 0); });
return out;
}
var [expandedAmpId, setExpandedAmpId] = React.useState(null);
var [hoveredExtra, setHoveredExtra] = React.useState(null); // for tooltip on +N
var displaySources = collapseLegacySources(sources);
return (
{displaySources.map(function (s) {
var mc = moodColor[s.mood || 'neutral'] || 'var(--text-tertiary)';
var highReach = (s.views || 0) >= 100000;
var ampN = (s.ampCount != null ? s.ampCount : (s.amplifiers ? s.amplifiers.length : 0));
var ampList = (s.amplifiers || []).slice(0, 3).map(function (a) { return '@' + a; }).join(' ');
var ampExtra = (s.amplifiers && s.amplifiers.length > 3) ? (s.amplifiers.length - 3) : 0;
var isExpanded = expandedAmpId === s.id;
var showTooltip = hoveredExtra === s.id && ampExtra > 0;
return (
{_dzh() ? '這些 cohort 成員放大了上面這則貼文。點他們的帳號打開個人檔案進一步調查。' : 'These cohort members amplified the post above. Click their handle to open profile and investigate further.'}
)}
{/* Simple hover tooltip for the +N extra handles */}
{showTooltip && (