Multi-Source Financial & General News

🚀 47 MILLION ROWS OF NEWS — one unified corpus for market-aware ML

We combined 15+ public news datasets (many small on their own) into one consistent, ready-to-use layer so you don’t have to wrangle them yourself. Everything is normalized to a minimal schema (✅ date, text, extra_fields) and shipped as Parquet shards per subset—streamable, DuckDB-friendly, and built with a backtest-safe dual-date policy.

This repo is finance-first (📰📈 earnings, macro, markets), but also includes broad general news—great for reinforcement learning, language modeling, retrieval/reranking, and event studies.

🤝 Why this exists: Most “big” news datasets for ML just didn’t exist when I started and I didn’t want to build a web-crawling pipeline, but there were lots of smaller public datasets scattered across Kaggle/HF/author zips. So I unified them into one consistent corpus that spans 1990–2024 and now totals 47,000,000+ rows. One place, one schema, no scraping—ready for stock trading RL, language modeling, retrieval, and more. 📰📈🧠

Why this matters

⏱️ Backtest-ready — day-level items carry a trading-session anchor to prevent look-ahead bias.
💾 Scale without pain — columnar Parquet, subset sharding, HF streaming support.
🔎 Provenance preserved — source metadata lives in extra_fields (URLs, publishers, tickers, etc.).

Note: I highly suggest turning this data into a local database (e.g., duckdb) if you want to use for RL training or any training for that matter where you need filtering/sorting capabilities that streaming does not adhere to.

One consolidated news corpus built from 15 public datasets, normalized into a single minimal schema and saved as Parquet shards per subset.

This repository hosts preprocessed Parquet shards organized by dataset-of-origin (data/<subset_name>/*.parquet). Each row contains:

date — UTC ISO-8601 string (minute-level if available; otherwise midnight UTC with trading anchor in extras)
text — canonicalized string (e.g., title + abstract or headline + article body)
extra_fields — compact JSON string with all preserved non-core fields (URL, publisher, authors, categories, tickers, provenance, timing details, etc.)
extra_fields.dataset — short identifier for the dataset-of-origin (e.g., fnspid_news, huffpost_news)

The goal is to provide a single point of access for multi-source news modeling, retrieval, and strategy research while preserving provenance and time handling for backtesting.

Note: There is most likely a lot of noise within this dataset (i.e., articles that don't matter), but think of it as part of the robustness testing your model training pipeline may need for stock trading tasks (or other uses)!

Contents (data)

Each subset corresponds to a processed folder/name in data/:

benzinga_6000stocks — Daily News 6000 Stocks (Benzinga): analyst ratings + headlines (2000s–2010s).
bloomberg_reuters — Bloomberg full-text (2006–2013) + Reuters titles (2007–2013).
sentarl_combined — SentARL used_icaif_2021 news (20 assets; headline+subhead+abstract; minute-level).
fnspid_news — FNSPID news portion only (1999–2023; very large; minute & day-level mixed).
mind_news_2019 — Microsoft MIND (2019; title+abstract); dates derived from behaviors first-seen when needed.
gold_news_kaggle — Commodity (Gold) annotated headlines (2000–2021).
huffpost_news — HuffPost News Category dataset (2012–2018; headlines).
sp500_daily_headlines — S&P 500 headlines (2008–2024; day-level).
djia_stock_headlines — DJIA “Daily News using Headlines” (2000–2016; Top1–Top25 per day flattened).
reddit_worldnews_2008_2016 — Reddit r/worldnews headlines (2008–2016; day-level).
wikinews_articles — Wikinews (open-licensed) articles; title + text; mixed years.
headlines_10sites_2007_2022 — 4.5M headlines from 10 major sites (2007–2022; date=YYYYMMDD).
nyt_headlines_1990_2020 — New York Times (1990–2020; headlines + metadata).
nyt_headlines_2010_2021 — New York Times (2010–2021; headline + abstract + lead paragraph).
cnbc_headlines — CNBC headlines with preview text (2017–2020).

Note: Coverage summaries above are approximate; see each subset’s original source for precise details. For licensing, assume research use only unless the source is explicitly open (e.g., Wikinews). Always attribute original sources.

Example rows (one per subset)

(Full, raw field selection. See the JSONL files in samples/.)

`benzinga_6000stocks`

{
  "date": "2009-02-14T19:02:00Z",
  "text": "How Treasuries and ETFs Work",
  "extra_fields": "{\"text_type\":\"headline\",\"time_precision\":\"minute\",\"tz_hint\":\"America/New_York\",\"dataset_source\":\"kaggle:miguelaenlle/massive-stock-news-analysis-db-for-nlpbacktests\",\"dataset\":\"benzinga_6000stocks\",\"source\":\"Benzinga\",\"raw_type\":\"analyst_ratings_processed\",\"stocks\":[\"NAV\"]}"
}

Saved full sample(s) to samples\benzinga_6000stocks_sample.jsonl.

`bloomberg_reuters`

{
  "date": "2006-10-20T20:16:16Z",
  "text": "-- Inco's Net Soars on Higher Metal Prices, Breakup Fee\n\nInco Ltd., the Canadian nickel producer\nbeing bought by Brazil 's Cia. Vale do Rio, said third-quarter\nprofit soared 11-fold, boosted by surging metal prices and fees\npaid by Falconbridge Ltd. after a failed takeover. \n Net income jumped to $701 million, or $3.08 a share, from $64\nmillion, or 29 cents, a year earlier, Toronto-based Inco said today\nin a statement. Results included $109 million in net fees from the\nfailed deals with Falconbridge and Phelps Dodge Corp. Sales jumped\nto $2.32 billion from $1.08 billion. \n Inco sold nickel at double the price last year on average, and\noutput jumped 13 percent. Demand for the metal, used in stainless\nsteel, surged as global economic growth fueled demand, especially\nin China . Mines have failed to keep pace, prompting a buying spree\nby producers seeking to bolster ore deposits. Vale outbid Phelps\nDodge and Teck Cominco Ltd. with its $17.3 billion bid. \n ``Record quarterly earnings reflect the unprecedented\nsustained strength we've seen in the nickel market, combined with\nstrong production,'' Inco Chief Executive Officer Scott Hand said\nin the statement. \n Shares of Inco gained 27 cents to C$85.85 at 4:10 p.m. on the\nToronto Stock Exchange. They have gained 80 percent in the past\nyear. Rio de Janeiro-based Vale, the world's largest iron-ore\nproducer, has offered C$86 a share for Inco. \n Breakup Fees \n Inco got $450 million from Falconbridge as a fee for their\nfailed merger, and made payments when deals failed with Phelps\nDodge and LionOre Mining International Ltd. A strike by workers at\nVoisey's Bay in September led to a $24 million charge in the third\nquarter, Inco said. \n Phelps Dodge, the world's third-biggest copper producer, in\nSeptember dropped its offer of cash and stock for Inco, whose\nshareholders supported an unsolicited cash bid from Vale. \n Inco's nickel production climbed to 125 million pounds in the\nquarter as prices jumped on average to $29,552 a metric ton. The\ncompany had cut its output forecast from as much as 140 million\npounds because of strikes and equipment failures. Cash costs for\nnickel sales fell 30 percent to $2.12 a pound, Inco said. \n Inco is the world's second-biggest nickel producer by 2005\noutput behind Russia 's OAO GMK Norilsk Nickel. \n Copper output rose 1.7 percent to 27,669 metric tons and\nprices jumped 90 percent on average to $7,465 a ton. \n Nickel today reached the highest since at least 1987 as\nsupplies lag behind demand. Inventories monitored by the London\nMetal Exchange plunged 86 percent this year. Mine output fell short\nof demand by 70,000 metric tons in the eight months ended August,\nthe World Bureau of Metal Statistics said. \n LME Nickel \n Nickel for delivery in three months gained $375, or 1.2\npercent, to $32,050 on the LME after reaching $32,625, the highest\nin at least 19 years. \n Extended repairs at operations in Indonesia and reduced output\nat a smelter in Sudbury, Ontario, forced Inco to cut its original\nproduction forecast for the quarter on Sept. 20. \n Inco has restored full production at Sudbury and a unit in\nManitoba has returned to ``stable operations'' after a damaged\nfurnace hurt output, Inco said. The company had said Sept. 21 it\nexpected to return to full production at Manitoba by early October. \n Inco declined to provide a forecast on earnings or production\nbefore the expiration of the CVRD offer on Oct. 23. \n Inco said it is ``continuing to review'' the cost and schedule\nfor the $2.15 billion Goro nickel project in New Caledonia that's\nbeen slowed by a general strike in the country. Inco expects to\nannounce a ``revised cost estimate'' and schedule by the end of the\nyear. \n ``There is a global shortage of skilled workers, which is felt\neven more acutely in New Caledonia with its population of 230,000\npeople,'' said Jeff Zweig, deputy general manager at Goro, in an e-\nmail on Oct. 16 ``To execute a project of this size and complexity,\na significant number of skilled workers are required.'' \n To contact the reporter on this story:\nDale Crofts in Chicago at \n [email protected] . \n To contact the editor responsible for this story:\nSteve Stroth at \n [email protected]",
  "extra_fields": "{\"author\":\"Dale Crofts\",\"url\":\"http://www.bloomberg.com/news/2006-10-20/inco-s-net-soars-on-higher-metal-prices-breakup-fee-update4-.html\",\"text_type\":\"full_article\",\"time_precision\":\"minute\",\"dataset_source\":\"no_longer_public\",\"dataset\":\"bloomberg_2006_2013\",\"source\":\"Bloomberg\",\"raw_type\":\"20061020_20131126_bloomberg_news\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\bloomberg_reuters_sample.jsonl.

`sentarl_combined`

{
  "date": "1997-01-03T14:39:00Z",
  "text": "U.S. stocks start the year on an upbeat note\n\nNEW YORK (MarketWatch) -- U.S. stocks rallied straight out of the gates on Wednesday, the first trading session of 2007, with the Dow Jones Industrial Average  boosted by better-than-expected holiday sales at Wal-Mart Stores Inc.  and news of a management shakeup at Home Depot Inc . The Dow was up 56 points at 12,520. The S&P 500 index  gained 5 points to 1,423 and the Nasdaq Composite  rose 19 points at 2,435. Home Depot gained 2.7% after news that its embattled chief executive, Robert Nardelli, resigned. Wal-Mart rose 2.9% after its December same store sales came ahead of expectations.",
  "extra_fields": "{\"stocks\":[\"$INDU\",\"$SPX\",\"COMP\",\"HD\",\"WMT\"],\"path_in_zip\":\"hd_2021-03-09T15:47:31_uptodate.csv\",\"text_type\":\"headline+subhead+abstract\",\"time_precision\":\"minute\",\"dataset_source\":\"author-provided\",\"dataset\":\"sentarl_20assets\",\"source\":\"SentARL\",\"raw_type\":\"used_icaif_2021_csv\",\"tz_hint\":\"America/New_York\"}"
}

Saved full sample(s) to samples\sentarl_combined_sample.jsonl.

`fnspid_news`

{
  "date": "2020-06-05T06:30:54Z",
  "text": "Stocks That Hit 52-Week Highs On Friday",
  "extra_fields": "{\"stocks\": [\"A\"], \"publisher\": \"Benzinga Insights\", \"author\": \"\", \"url\": \"https://www.benzinga.com/news/20/06/16190091/stocks-that-hit-52-week-highs-on-friday\", \"text_type\": \"headline+article\", \"time_precision\": \"minute\", \"dataset_source\": \"huggingface:Zihan1004/FNSPID\", \"dataset\": \"fnspid_news\", \"raw_type\": \"fnspid_news_csv\", \"tz_hint\": \"America/New_York\"}"
}

Saved full sample(s) to samples\fnspid_news_sample.jsonl.

`mind_news_2019`

{
  "date": "2019-11-09T00:00:00Z",
  "text": "Chris Wallace reacts after frontrunner Warren releases $52 trillion Medicare for All plan\n\n'Fox News Sunday' anchor Chris Wallace says Democratic presidential candidate Elizabeth Warren's $52 trillion Medicare for All plan is enormously risky.",
  "extra_fields": "{\"date_source\":\"fallback_global_min_midnight\",\"time_precision\":\"day_fallback\",\"date_first_seen\":null,\"url\":\"https://assets.msn.com/labs/mind/AAJIcNo.html\",\"text_type\":\"title+abstract\",\"dataset_source\":\"msnews.microsoft.com\",\"dataset\":\"mind_news_2019\",\"source\":\"MSN\",\"raw_type\":\"MIND_news_tsv\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\mind_news_2019_sample.jsonl.

`gold_news_kaggle`

{
  "date": "2000-02-15T00:00:00Z",
  "text": "gold is poised for greatness",
  "extra_fields": "{\"date_raw\":\"15-02-2000\",\"date_trading\":\"2000-02-16T14:30:00Z\",\"url\":\"http://www.marketwatch.com/story/thom-calandras-stockwatch-gold-is-poised-for-greatness-2000-02-15\",\"text_type\":\"headline\",\"dataset_source\":\"kaggle:ankurzing/sentiment-analysis-in-commodity-market-gold\",\"time_precision\":\"day\",\"anchor_policy\":\"date_midnight_utc + next_open_in_date_trading\",\"dataset\":\"gold_news_kaggle\",\"raw_type\":\"kaggle_gold_news_csv\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\gold_news_kaggle_sample.jsonl.

`huffpost_news`

{
  "date": "2012-01-28T00:00:00Z",
  "text": "Dwight Howard Rips Teammates After Magic Loss To Hornets\n\nThe five-time all-star center tore into his teammates Friday night after Orlando committed 23 turnovers en route to losing",
  "extra_fields": "{\"category\":\"SPORTS\",\"authors\":\"\",\"date_raw\":\"2012-01-28\",\"date_trading\":\"2012-01-30T14:30:00Z\",\"link\":\"https://www.huffingtonpost.com/entry/dwight-howard-rips-teammates-magic-hornets_us_5bb69b24e4b097869fd1b331\",\"text_type\":\"headline+summary\",\"dataset_source\":\"kaggle:rmisra/news-category-dataset\",\"time_precision\":\"day\",\"anchor_policy\":\"date_midnight_utc + next_open_in_date_trading\",\"dataset\":\"huffpost_news_categories\",\"source\":\"HuffPost\",\"raw_type\":\"huffpost_jsonl\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\huffpost_news_sample.jsonl.

`sp500_daily_headlines`

{
  "date": "2008-01-02T00:00:00Z",
  "text": "JPMorgan Predicts 2008 Will Be \"Nothing But Net\"",
  "extra_fields": "{\"date_raw\":\"2008-01-02\",\"date_trading\":\"2008-01-03T14:30:00Z\",\"text_type\":\"headline\",\"dataset_source\":\"kaggle:dyutidasmahaptra/s-and-p-500-with-financial-news-headlines-20082024\",\"time_precision\":\"day\",\"anchor_policy\":\"date_midnight_utc + next_open_in_date_trading\",\"dataset\":\"sp500_daily_headlines\",\"source\":\"market_recaps\",\"raw_type\":\"sp500_headlines_csv\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\sp500_daily_headlines_sample.jsonl.

`reddit_worldnews_2008_2016`

{
  "date": "2008-06-08T00:00:00Z",
  "text": "b'Marriage, they said, was reduced to the status of a commercial transaction in which women could be discarded by husbands claiming to have discovered hidden defects in them.'",
  "extra_fields": "{\"date_raw\":\"2008-06-08\",\"date_trading\":\"2008-06-09T13:30:00Z\",\"text_type\":\"headline\",\"time_precision\":\"day\",\"anchor_time_local\":\"09:30:00\",\"backtest_rule\":\"shift_to_next_trading_day\",\"dataset_source\":\"kaggle:tanishqdublish/stock-market-predictions\",\"anchor_policy\":\"date_midnight_utc + next_open_in_date_trading\",\"dataset\":\"reddit_worldnews_2008_2016\",\"source\":\"Reddit (r/worldnews)\",\"raw_type\":\"RedditNews_csv\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\reddit_worldnews_2008_2016_sample.jsonl.

`djia_stock_headlines`

{
  "date": "2000-01-03T00:00:00Z",
  "text": "A 'hindrance to operations': extracts from the leaked reports",
  "extra_fields": "{\"top_index\":\"top1\",\"date_raw\":\"2000-01-03\",\"date_trading\":\"2000-01-04T14:30:00Z\",\"text_type\":\"headline\",\"dataset_source\":\"kaggle:lykin22/stock-headlines\",\"time_precision\":\"day\",\"anchor_policy\":\"date_midnight_utc + next_open_in_date_trading\",\"dataset\":\"djia_stock_headlines\",\"source\":\"DJIA_daily_headlines\",\"raw_type\":\"djia_stock_headlines_csv\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\djia_stock_headlines_sample.jsonl.

`wikinews_articles`

{
  "date": "2002-04-01T00:00:00Z",
  "text": "Department of Defense report lambasts communication failure in US War on Terror\n\nA U.S. Department of Defense\nadvisory committee has released a report harshly criticizing the U.S.-led \"War\non Terror\". The report details communication failures with the Muslim\nworld, and notes that current efforts may have achieved the opposite\nof their intended effect.\n\nThe report released without publicity the Wednesday before Thanksgiving by Defense Science Board, focuses on a failure of communication, which the Defense Science Board considers vital to the war on terror. It asserts this failure of \"strategic communication\" contributes to a perceived \"negative image in world opinion and diminished ability to persuade\" of the United States, and that a resulting atmosphere of hostility can manifest in numerous ways.\n\nThe list of harmful effects includes \"terrorism, thin coalitions, harmful effects on business, restrictions\non travel, declines in cross border tourism and education flows, and\ndamaging consequences for other elements of U.S. soft power\".\n\nAccording to the report, \"The information campaign ... is an essential objective, because the larger goals of U.S. strategy depend on separating the vast majority of non-violent Muslims from the radical-militant Islamist-Jihadists. But American efforts have not only failed in this respect: they may also have achieved the opposite of what they intended.\"\n\nBy way of example, the report quotes figures from a June 2004 Zogby poll, claiming to show a significant drop in Arab support for the U.S. in the past couple years. Statistical results are reproduced below.\n\nThe report further claims, \"American direct intervention in the Muslim World has paradoxically elevated the stature of and support for radical Islamists.\" As summarised in a Christian Science Monitor headline, 'They hate our policies, not our freedom'.\n\nSo why has support for the U.S. dropped? -- to single digits in some Arab nations. President Bush and others have famously claimed that America is hated for its freedom. But the Defense Science Board concluded that most Arabs \"do not hate us for our values, but because of our policies.\" From the same Zogby study:\n\nThis study explains that while support for American values may not be overwhelming, it is practically non-existent for America's policies in the Middle East.\n\n\"The overwhelming majority voice their objections to what they see as one-sided support in favor of Israel and against Palestinian rights, and the longstanding, even increasing support for what Muslims collectively see as tyrannies, most notably Egypt, Saudi Arabia, Jordan, Pakistan, and the Gulf states. Thus when American public diplomacy talks about bringing democracy to Islamic societies, this is seen as no more than self-serving hypocrisy.\"\n\nIn the eyes of Muslims, according to this report, America is really only looking out for its own interests.\n\nIt concludes from this that the fundamental problem with relations with the Muslim world is not a simple matter of crafting the right message. \"Rather, it is a fundamental problem of credibility. Simply, there is none.\"",
  "extra_fields": "{\"categories_norm\":[\"middle east\",\"lebanon\",\"north america\",\"religion\",\"united arab emirates\",\"united states\",\"saudi arabia\",\"islam\",\"jordan\",\"tourism\",\"us war on terror\",\"morocco\",\"egypt\",\"africa\"],\"date_raw\":\"2002-04-01\",\"date_trading\":\"2002-04-02T14:30:00Z\",\"text_type\":\"title+article\",\"dataset_source\":\"kaggle:datagator/wikinews-article-dataset\",\"time_precision\":\"day\",\"anchor_policy\":\"date_midnight_utc + next_open_in_date_trading\",\"dataset\":\"wikinews_articles\",\"source\":\"Wikinews\",\"raw_type\":\"wikinews_json\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\wikinews_articles_sample.jsonl.

`headlines_10sites_2007_2022`

{
  "date": "2007-01-01T00:00:00Z",
  "text": "Rush to Hang Hussein Was  Questioned",
  "extra_fields": "{\"publication\": \"New York Times\", \"date_raw\": \"2007-01-01\", \"date_trading\": \"2007-01-03T14:30:00Z\", \"url\": \"http://www.nytimes.com/2007/01/01/world/middleeast/01iraq.html?hp&ex=1167714000&en=85dae91ed8178e3a&ei=5094&partner=homepage\", \"text_type\": \"headline\", \"date_source\": \"YYYYMMDD\", \"dataset_source\": \"kaggle:jordankrishnayah/45m-headlines-from-2007-2022-10-largest-sites\", \"time_precision\": \"day\", \"anchor_policy\": \"date_midnight_utc + next_open_in_date_trading\", \"dataset\": \"headlines_10sites_2007_2022\", \"raw_type\": \"10sites_headlines_csv\", \"tz_hint\": \"UTC\"}"
}

Saved full sample(s) to samples\headlines_10sites_2007_2022_sample.jsonl.

`nyt_headlines_1990_2020`

{
  "date": "1990-01-01T05:00:00Z",
  "text": "Bridge",
  "extra_fields": "{\"news_desk\":\"Metropolitan Desk\",\"url\":\"https://www.nytimes.com/1990/01/01/nyregion/bridge-173390.html\",\"text_type\":\"headline\",\"time_precision\":\"minute\",\"dataset_source\":\"kaggle:johnbandy/new-york-times-headlines\",\"dataset\":\"nyt_headlines_1990_2020\",\"source\":\"New York Times\",\"raw_type\":\"nyt_csv\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\nyt_headlines_1990_2020_sample.jsonl.

`nyt_headlines_2010_2021`

{
  "date": "2007-07-07T14:46:20Z",
  "text": "It was a long antipodean night. While there’s no telling what’s a reflection of national taste and what’s the result of booking expediency, each of the concerts from Australia, Japan and China certainly had its own character.\n\nLive Earth: Earnest Crooners and a “Supersonic Speed Machine” in Australia, China and Japan\n\nIt was a long antipodean night. While there’s no telling what’s a reflection of national taste and what’s the result of booking expediency, each of the concerts from Australia, Japan and China certainly had its own character.",
  "extra_fields": "{\"news_desk\":\"Culture\",\"section\":null,\"section_name\":\"Arts\",\"byline\":null,\"url\":null,\"text_type\":\"abstract+headline+lead\",\"time_precision\":\"minute\",\"dataset_source\":\"kaggle:tmishinev/nyt-headlines-20102021\",\"dataset\":\"nyt_headlines_2010_2021\",\"source\":\"New York Times\",\"raw_type\":\"nyt_2010_2021_csv\",\"tz_hint\":\"UTC\"}"
}

Saved full sample(s) to samples\nyt_headlines_2010_2021_sample.jsonl.

`cnbc_headlines`

{
  "date": "2006-11-30T14:25:19Z",
  "text": "Word On The Street: The Day Ahead\n\nTime for our look at the day ahead--with \"Word on the Street.\" On this morning's \"Squawk On The Street\" --CNBC’s Mark Haines spoke with Peter Costa-Senior Managing Director at Lipari Partners.  Costa says he's going to develop his own theory--\"Costa's Theory of  Economic Confusion\" -- from this week's information. He says it's kind of hard to figure out what direction the market will move today.He added that he's been a bull all year and he expects markets to go higher for the rest of the 2006.",
  "extra_fields": "{\"author\":\"Lee Brodie\",\"publisher\":\"CNBC\",\"category\":\"CNBC TV\",\"url\":\"https://www.cnbc.com/2006/11/30/word-on-the-street-the-day-ahead.html\",\"text_type\":\"headline+abstract\",\"time_precision\":\"minute\",\"dataset_source\":\"kaggle:crawlfeeds/cnbc-news-headlines-dataset\",\"dataset\":\"cnbc_headlines_2017_2020\",\"source\":\"CNBC\",\"raw_type\":\"cnbc_csv\",\"tz_hint\":\"America/New_York\"}"
}

Saved full sample(s) to samples\cnbc_headlines_sample.jsonl.

Unified schema

All subsets share the same minimal schema:

Column	Type	Description
`date`	string	UTC timestamp in ISO 8601 (`YYYY-MM-DDTHH:MM:SSZ`). If original precision is only day-level, the top-level `date` is set to midnight UTC and trading-anchor information is kept in `extra_fields` (see below).
`text`	string	Canonicalized text (e.g., title + two newlines + body/abstract). Paragraph breaks are preserved; long runs of whitespace normalized.
`extra_fields`	string	JSON string bundling all preserved non-core fields (URL(s), publisher(s), author(s), tickers, categories, provenance, and timing metadata).
`extra_fields.dataset`	string	Subset identifier (dataset-of-origin).

Timing policy (minute vs day level)

Minute-level inputs are converted to UTC ISO strings. Known local strings (e.g., EST/EDT) are localized to America/New_York and converted to UTC.
Day-level inputs follow the dual-date policy:
- top-level date = midnight UTC for display and coarse alignment
- extra_fields includes:
  - date_raw — raw date as provided
  - date_trading — the NYSE market open time (usually 09:30 ET) of the next trading session (T+1) in UTC (configurable; we used next-day anchoring to avoid lookahead bias when true publish time is unknown)
  - anchor_time_local, backtest_rule, and tz_hint for transparency

This policy ensures time-aware backtesting without implying a specific intra-day minute when only day precision exists.

URL & text normalization

URLs are canonicalized (strip fragments and utm_* tracking params).
Text is trimmed, Windows newlines normalized, repeated blank lines collapsed, and long spaces compressed; paragraph structure preserved.

Deduplication

Within most loaders we apply (date, normalized text) deduplication and union tickers/URLs/publishers where appropriate.
Cross-subset duplicates are expected (e.g., syndicated headlines). Users can run their own global dedupe across all subsets if needed (e.g., on (date, text) or normalized url).

How to load

This repo requires an account and to login for use (huggingface-cli login; see source)

1) Install

pip install datasets

2) Load everything (streaming is recommended given the size of the data)

from datasets import load_dataset

# All shards across all subsets:
ds = load_dataset(
    path="Brianferrell787/financial-news-multisource",           
    data_files="data/*/*.parquet",
    split="train",
    streaming=True
)

for i, row in enumerate(ds):
    # row["extra_fields"] is a JSON string
    if i == 3:
        break

3) Load a single subset

from datasets import load_dataset
huff = load_dataset("Brianferrell787/financial-news-multisource",
                    data_files="data/huffpost_news/*.parquet",
                    split="train",
                    streaming=True)

4) Load multiple chosen subsets

files = [
    "data/fnspid_news/*.parquet",
    "data/bloomberg_reuters/*.parquet",
    "data/cnbc_headlines/*.parquet",
]
ds = load_dataset("Brianferrell787/financial-news-multisource", data_files=files, split="train", streaming=True)

5) Parse extras

import json
sample = next(iter(ds))
extras = json.loads(sample["extra_fields"])
print(extras.get("url"), extras.get("publisher"), extras.get("date_trading"))

Tip: If you prefer non-streaming, omit streaming=True. Parquet enables columnar, memory-efficient reads even at scale.

Example: backtest-safe date handling

Day-level rows carry two timestamps:

date (top-level): midnight UTC (YYYY-MM-DDT00:00:00Z), used for coarse alignment/joins.
extra_fields.date_trading: NYSE next-session open in UTC (default). Use this for labeling or event-time alignment in backtesting.

def event_time_utc(row):
    import json, datetime
    extra = json.loads(row["extra_fields"])
    return extra.get("date_trading") or row["date"]

You can switch to same-day anchoring if desired; we recorded the policy in extra_fields.backtest_rule.

Provenance & subset notes

We preserve source metadata inside extra_fields, including (where available): url / urls, publisher / publishers, author, stocks (tickers), category/subcategory, news_id, precomputed summaries, and dataset-specific fields (e.g., MIND entities). Examples:

FNSPID: minute/day-level mixed; we use only the news CSVs; stocks & summaries preserved.
MIND: publish time rarely present; we derive date from earliest impression timestamp in behaviors.tsv when available, else use fallback midnight within the logged window.
Reuters titles: optionally day-anchored (T+1 @ 09:30 ET) depending on configuration; here we stored the chosen rule in backtest_rule.
Wikinews: open license; we keep title + full text where provided.

A quick per-subset description appears near the top of this card. Please consult the original sources for licensing and intended use.

Intended use & licensing

This corpus is meant for research: LLM pretraining/fine-tuning, retrieval, event studies, and backtesting of news-driven strategies.
Original content remains the property of the respective publishers/data providers. Redistribution of full text may require permission.
The maintainers provide this aggregated format as research-only preprocessing. If you are a rightsholder and would like content removed, please open an issue or email the maintainers.

Openly licensed content: Wikinews is CC-licensed; retain attribution and abide by its terms.

Dataset creation pipeline (summary)

Download original data (Kaggle/HF/archives).
Standardize to (date, text, extra_fields) with dataset-specific parsers.
Time handling: minute-level → UTC; day-level → dual-date policy (midnight top-level + trading anchor in extras).
Normalize: URL hygiene; conservative text normalization.
Deduplicate per subset on (date, normalized text) with union of tickers/urls/publishers where applicable.
Export Parquet shards per subset → upload to the Hub.

Where necessary (e.g., MIND), timestamps are derived (first-seen from behaviors) or fallback to a safe default (documented in extras).

Known limitations

Cross-subset duplicates are expected; syndicated content appears multiple times.
Some rows lack URLs or precise times; we document the chosen anchoring in extra_fields.
Ticker coverage is uneven; use extra_fields.stocks if present.

Versioning

v0.1.0 — Initial unified release; 15 subsets; Parquet shards per subset; dual-date policy for day-level rows.

If there are any updates/edits or even other news datasets to add you have in mind, let me us know!

How to cite

If you use this dataset, please cite the original sources and this unified release. A generic BibTeX entry for the unified format:

@dataset{unified_news_multi_source_2025,
  title        = {Multi-Source Financial \& General News},
  author       = {Ferrell, Brian},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/datasets/Brianferrell787/financial-news-multisource}},
  note         = {Preprocessed multi-source news corpus}
}

Maintainers & contact

Maintainer: [email protected]
Issues and takedown requests: open a discussion on the dataset repo or email us.

Quick QA

Q: Why midnight UTC for day-only rows?
A: To avoid implying any exact intra-day minute and to keep merges stable across sources. Backtest with extra_fields.date_trading.

Q: Are there splits?
A: No fixed train/val/test. This is a document store. Use time-based splits or subset-based splits as needed.

Q: Can I stream only finance-focused sources?
A: Yes—pass specific data_files globs to load_dataset (see examples).

Q: What’s inside extra_fields?
A: A compact JSON with everything not in date/text/dataset, e.g.:

{
  "url": "https://example.com/news/123",
  "publisher": "Reuters",
  "author": "Jane Doe",
  "stocks": ["AAPL","MSFT"],
  "category": "business",
  "time_precision": "day",
  "date_raw": "2011-04-19",
  "date_trading": "2011-04-20T13:30:00Z",
  "anchor_time_local": "09:30:00",
  "backtest_rule": "shift_to_next_trading_day",
  "dataset_source": "kaggle:some/source"
}

Loading cheatsheet

# ALL
load_dataset("Brianferrell787/financial-news-multisource", data_files="data/*/*.parquet", split="train", streaming=True)

# One subset
load_dataset("Brianferrell787/financial-news-multisource", data_files="data/fnspid_news/*.parquet", split="train")

# Two subsets
load_dataset("Brianferrell787/financial-news-multisource", data_files=["data/cnbc_headlines/*.parquet",
                                               "data/huffpost_news/*.parquet"],
             split="train")

# Pandas-style: take a slice quickly
ds = load_dataset("Brianferrell787/financial-news-multisource", data_files="data/nyt_headlines_2010_2021/*.parquet", split="train")
df = ds.shuffle(seed=42).take(1000)  # or use .to_pandas() for small samples

Datasets:

Brianferrell787
/

financial-news-multisource

Request access to Multi-Source Financial & General News