SocialINTEL
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Every enrichment field is produced by deterministic, auditable algorithms — VADER lexicon scoring, keyword/regex pattern matching, and heuristic formulas. No black boxes. Every score is reproducible from source code.
Content first passes through the Content Gate (has_content / content_too_short) — empty or too-short posts return minimal fields immediately, skipping all downstream computation. Gated posts proceed through language detection → VADER sentiment → emotion → quality scoring → classification → entity extraction → engagement → signal detection → domain-specific extraction → aspect sentiment → composite scores → quality control. Each stage depends on the previous: if the language gate blocks VADER, all downstream sentiment/emotion fields are zeroed.
“I can't believe how amazing GPT-5 is. The reasoning capabilities are light-years ahead of GPT-4. OpenAI has completely changed the game. This is going to revolutionize everything. And it's open source too! Absolutely incredible.”
This shows how the pipeline transforms raw text into structured, queryable signals — from sentiment and emotion through topic classification, entity extraction, domain-specific AI/ML fields, writing style detection, and even financial sentiment inference. Every value was computed deterministically — no LLMs, no external APIs.