HN company-mention sentiment (daily)

Daily enrichment signals scoring how Hacker News talks about ~70 US and Canadian companies. Each day the official keyless HN search API (Algolia) supplies the current front page plus every story submitted in the trailing 24 hours; a curated company dictionary (name, primary-listing ticker, HQ country, aliases, link domains) resolves mentions on title + selftext + URL host, and a documented deterministic valence lexicon (negation and intensifier rules, no model, no network) scores each mentioning story. Per company and day: mention_count, story_ids, total_points (HN points collected — an attention proxy), mean_sentiment (unweighted mean story sentiment), weighted_sentiment (points-weighted), pos_share / neg_share (fraction of mentioning stories with sentiment > 0.12 / < -0.12), the top story's title, and buzz_score = 100 * (50% min-max-normalized mention count + 50% min-max-normalized log10(total points + 1)), ranked as attention_rank (1 = hottest; ties: mention count desc, company name asc). Who joins this: a quant desk or investor-relations team joins per-ticker daily tech sentiment to their positions/returns table on ticker + as_of; a comms team joins on company_name to their media-monitoring calendar. Primary key: (as_of, company_name); join keys: ticker, company_name, as_of, country_code (ISO alpha-3). Nullability: ticker is null for private companies (OpenAI, Anthropic, Stripe, ...); top_story_title is never null. Caveats: sentiment is computed from story titles + selftext only (comments are not fetched — that would multiply requests ~100x); story-level sentiment is a lexicon mean, not a model judgment; buzz_score is a within-snapshot relative measure, not comparable across days; HN skews toward software/AI topics, so hardware/retail names are sparser. Sample use: filter ticker = 'NVDA' for Nvidia's daily HN sentiment, or order by attention_rank for today's most-buzzed companies.

Les titres et les descriptions proviennent des sources de données, en anglais.