The Atlantic Archive (1857–1930)

Complete pre-1930 archive of The Atlantic, America's most enduring literary and cultural magazine, founded in 1857 by Emerson, Longfellow, Holmes, and other literary giants. **240,011 rows** of clean, structured text spanning from the first volume through 1930.

**What this data does for your model:**

- Your model learns authentic 19th‑century literary voice from Emerson, Longfellow, Holmes, and other founding contributors.
- Your model retrieves actual Gilded Age social commentary on architecture, domestic life, politics, and cultural norms.
- Your model trains on serialized fiction, fairy tales, and literary prose as originally published.
- Your model understands the evolution of American magazine writing from moral essays to cultural criticism.

**Includes:** Volume 1, Number 1 (1857) through 1930.<br/>**Total rows:** 240,011

**What's inside:**

- Literary fiction and poetry from America's greatest writers
- Cultural criticism and social commentary
- Essays on politics, philosophy, and science
- Domestic architecture and design criticism
- Fairy tales and serialized fiction

**Perfect for:**

- LLM fine-tuning on 19th-century American literature
- Cultural history and literary criticism
- Digital humanities and periodical studies
- Journalism and media history research

**Format:** Snowflake-native JSONL with columns: ISSUE, TITLE, AUTHOR, TYPE, TEXT. Fully cleaned, bias-audited, and ready for AI training.

*From Emerson to the Great Depression, the magazine that shaped American letters, now ready for AI.*

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原始信息汇总

数据集概述：The Atlantic Archive (1857–1930)

基本信息

• 数据集名称：The Atlantic Archive (1857–1930)
• 提供方：Devin Media Corp.
• 数据规模：240,011 行，涵盖从首卷到1930年的完整、结构化文本。
• 数据格式：Snowflake-native JSONL，包含字段：ISSUE、TITLE、AUTHOR、TYPE、TEXT。
• 数据质量：经过专业清洗、偏差审核，可直接用于AI训练。
• 更新频率：每年更新一次。
• 交付方式：安全共享（Secure share）。

数据内容

包含《大西洋月刊》自1857年创刊至1930年的完整档案，涵盖以下内容类型：

• 文学小说与诗歌（来自美国最伟大作家）
• 文化批评与社会评论
• 政治、哲学与科学论文
• 国内建筑与设计批评
• 童话与连载小说

适用场景

• LLM微调：用于19世纪美国文学领域的大语言模型微调。
• 文化历史与文学批评：支持文化史和文学批评研究。
• 数字人文学科：适用于期刊研究和数字人文学分析。
• 新闻与媒体历史研究：用于媒体史和新闻史研究。

商业需求匹配

• 机器学习：用于训练、微调及部署机器学习模型，适合领域特定LLM微调、文学术语提取和文化自然语言处理。
• 真实世界数据（RWD）：提供1857–1930年间美国知识生活的历史记录，用于研究分析。
• 生命科学商业化：支持人文学科研究，记录美国文学从战前时期到1930年的演变。

使用示例（SQL查询）

• 查看元数据文档：SELECT TITLE, TEXT FROM ATLANTIC_CORPUS WHERE TYPE = metadata LIMIT 5;
• 搜索文学内容：SELECT ISSUE, TITLE, AUTHOR FROM ATLANTIC_CORPUS WHERE TYPE = article AND TEXT ILIKE %poetry% OR TEXT ILIKE %fiction% OR TEXT ILIKE %essay% LIMIT 10;
• 按类型统计行数：SELECT TYPE, COUNT(*) FROM ATLANTIC_CORPUS GROUP BY TYPE;
• 查看1857年首卷：SELECT TITLE, ISSUE, AUTHOR FROM ATLANTIC_CORPUS WHERE TYPE = article AND ISSUE LIKE 1857% LIMIT 10;
• 搜索文化批评：SELECT TITLE, AUTHOR, ISSUE FROM ATLANTIC_CORPUS WHERE TYPE = article AND TEXT ILIKE %architecture% OR TEXT ILIKE %domestic% OR TEXT ILIKE %society% LIMIT 10;

分类标签

• AI & ML
• Life Sciences Commercialization
• Machine Learning
• Real World Data (RWD)

联系方式

• 销售与支持：[e-mail]