SocialINTEL
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Turn raw social content into analysis-ready datasets with 150+ enrichment fields across 14 technique categories. Methodology Documentation
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Any dataset under 10,000 records is free to download in full — no account, no card. As we collect more data, these grow into paid datasets. Grab them while they're free.
A structured table of rows and columns — like a spreadsheet. Each row is one piece of content (a post, repo, video), and each column is a field like title, date, likes, or sentiment score.
Raw social data isn't very useful alone. Enrichment means each row has been run through ML models to add useful signals: sentiment, topics, trending scores, extracted entities.
Developers feeding data into LLMs. Researchers studying online discourse. Analysts tracking market sentiment. Anyone who needs clean social data without building a scraper.
Millions of posts, repos, videos, and articles captured from Reddit, GitHub, YouTube, LinkedIn, and 75+ more platforms every day.
Sentiment scoring, topic tagging, salary extraction, trending signals, virality scores — whatever the dataset needs.
Clean CSV, JSON, or Parquet. Load into Python, Excel, Tableau, or feed straight into your model. No scraping needed.
| id | content | url | author | author_id | author_followers | author_verified | published_at | collected_at | platform | likes | comments | shares | views | engagement_rate | hashtags | mentions | active_modules | sentiment_label | sentiment_score | sentiment_confidence | sentiment_method | emotion_primary | emotion_secondary | sarcasm_flag | tone | language_detected | subjectivity_score | intensity_score | toxicity_score | topic_tags | virality_score | trending_signal | trending_rank | original_platform | duplicate_hash | enriched_at | finance_topic | asset_class | investment_strategy | target_demographic | goal_type | debt_topic | fire_mentioned | inflation_signal |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Just closed on my first home. Rates finally dipped below 6% and sellers are getting realistic on price. | link | firsttimebuyer | u123 | 350 | false | 2026-05-28T14:30:00Z | 2026-05-28T15:00:00Z | 1840 | 320 | 45 | 52000 | 6.3% | firsttimehomebuyer,realestate | sentiment,topic,finance | positive | 0.82 | 0.91 | roberta-base | joy | relief | false | informal | en | 0.75 | 0.62 | 0.01 | real-estate,first-time-buyer,mortgage-rates | 0.34 | false | a1b2c3d4e5f6… | 2026-05-28T15:05:00Z | real estate | real-estate | passive | retail | wealth-building | true | false | false | ||||
| 2 | Three price cuts and still no offers. Insurance alone is now $600/mo in Florida. Who can afford this? | link | frustratedseller | u456 | 180 | false | 2026-05-28T16:45:00Z | 2026-05-28T17:20:00Z | 2100 | 580 | 120 | 78000 | 15.6% | realestate,sellersmarket | sentiment,topic,finance | negative | -0.71 | 0.88 | roberta-base | frustration | anxiety | false | informal | en | 0.85 | 0.73 | 0.02 | real-estate,price-cuts,insurance | 0.52 | true | 42 | f6e5d4c3b2a1… | 2026-05-28T17:25:00Z | real estate | real-estate | active | retail | income | true | false | true |
We'll collect any social media data you need across 75 platforms — delivered in 3–7 days.
100 rows. No signup. See the quality yourself or grab a full free dataset.