Alternative data datasets
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Short data analytics project about the google trends interest of AI & LLM
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EarningsSignal: Earnings Call Tone & Guidance Classification Dataset
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Analytical outputs capturing sentiment, emotional tone, intensity, and controversial elements found in online video material.
Quarterly conference calls are processed to detect revisions in guidance and shifts in executive language.
S&P 500 earnings-call transcripts in Parquet under MIT, tens of thousands of calls. Independently compiled and comparable to other public transcript corpora for sentiment and tone work.
Tone indicators extracted from onshore research publications originating in China.
Project intelligence on energy infrastructure covering pipelines, commodity facilities, permits and construction milestones.
GDELT, a long-running global news monitoring effort tracking events, tone and geographic references with fifteen-minute refresh cycles.
Earnings-call transcripts from an IBM research project, tens of thousands of records with finance tags, in CC0. A filings-adjacent corpus for call-tone and question-and-answer analysis.
Earnings-call transcripts for S&P 500 companies, tens of thousands of calls in English with timestamps, in Parquet (MIT). Direct input for call-tone and question-and-answer sentiment analysis across the large-cap earnings cycle.
Organized intelligence drawn from news outlets and social platforms exceeding forty thousand in number, including tone and sentiment analysis.
A community-compiled collection of stock-market-related tweets in English, stored as CSV, hundreds of thousands of posts (CC BY 4.0). Retail chatter feeds sentiment-signal research and market-tone studies.
A machine learning service evaluates online material to assign sentiment and emotional tone scores.