Poetry-Foundation-Poems

From: https://www.kaggle.com/datasets/tgdivy/poetry-foundation-poems

**Poetry Foundation Poems Dataset**

**Overview**

This dataset contains a collection of 13.9k poems sourced from the Poetry Foundation website. Each poem entry includes its title, author, and associated tags (if available). The dataset provides a robust resource for exploring poetry, analyzing thematic trends, or creating applications such as poem generators.

**Dataset Structure**

The dataset consists of the following columns:

1. Title: The title of the poem.

2. Author: The name of the poem’s author.

3. Tags: The thematic tags or categories associated with the poems.

Dataset Highlights

• Size: The dataset includes 13.9k rows, with each row representing an individual poem.

• Diversity: Poems span a wide range of topics and authors, making it a rich resource for literary and thematic exploration.

• Tags: The tags provide a structured way to categorize and filter poems by themes, enhancing the dataset’s usability for research and creative projects.

**Use Cases**

1. Poem Generation:

Train models to generate poems based on user-inputted topics or tags.

2. Thematic and Sentiment Analysis:

Analyze trends in poetic themes, sentiments, or styles over time.

3. NLP Tasks:

Use the dataset for text classification, clustering, or other natural language processing tasks.

4. Educational Resources:

Develop tools or applications for poetry analysis, learning, or teaching.

5. Visualizations:

Create word clouds or charts using the tags to identify common themes in poetry.

**Technical Details**

• File Size: Approximately 13,900 rows of data.

• Format: Typically provided in CSV or JSON format.

• Dependencies:

• Pandas for data manipulation.

• NLTK or spaCy for natural language processing.

• Matplotlib or WordCloud for creating visualizations.

**Licensing**

This dataset is under **GNU Affero General Public License v3.0**.

**Acknowledgments**

The dataset was compiled to provide researchers, developers, and enthusiasts with a structured collection of poetry for creative and analytical purposes. All credits go to the original authors and the Poetry Foundation for their work in making these poems accessible.

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数据来源：https://www.kaggle.com/datasets/tgdivy/poetry-foundation-poems

**诗歌基金会诗歌数据集（Poetry Foundation Poems Dataset）**

**概览**
本数据集收录了源自诗歌基金会官网的13900首诗歌。每条诗歌条目包含标题、作者以及相关标签（如有提供）。本数据集为诗歌探索、主题趋势分析或开发诗歌生成器等应用提供了可靠的优质资源。

**数据集结构**
本数据集包含以下列：
1. Title（标题）：诗歌的标题。
2. Author（作者）：诗歌作者的姓名。
3. Tags（标签）：与诗歌相关的主题标签或分类类别。

**数据集亮点**
• 规模：本数据集包含13900条数据记录，每条记录对应一首独立诗歌。
• 多样性：收录的诗歌涵盖广泛的主题与作者群体，是开展文学与主题探索的丰富资源。
• 标签体系：标签提供了结构化的分类与筛选方式，可按主题对诗歌进行归类与过滤，有效提升了本数据集在研究与创意项目中的可用性。

**应用场景**
1. 诗歌生成：
训练模型基于用户输入的主题或标签生成诗歌。
2. 主题与情感分析：
分析不同时期诗歌的主题、情感或风格趋势。
3. 自然语言处理（Natural Language Processing，简称NLP）任务：
将本数据集用于文本分类、聚类或其他自然语言处理任务。
4. 教育资源：
开发用于诗歌分析、学习或教学的工具与应用程序。
5. 可视化创作：
利用标签生成词云或图表，以识别诗歌中的常见主题。

**技术细节**
• 数据规模：约13900条数据记录。
• 文件格式：通常以CSV或JSON格式提供。
• 依赖工具：
• Pandas：用于数据处理与操作。
• NLTK或spaCy：用于自然语言处理任务。
• Matplotlib或WordCloud：用于生成可视化内容。

**授权协议**
本数据集采用**GNU Affero通用公共许可证v3.0（GNU Affero General Public License v3.0）**。

**致谢**
本数据集的编制旨在为研究人员、开发者与诗歌爱好者提供结构化的诗歌合集，用于创意与分析用途。所有荣誉归于原作者及诗歌基金会，感谢他们将这些诗歌公开传播，使其得以被广泛获取。

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