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Academic Papers Metadata Collection
Education & Learning Analytics
Tags and Keywords
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Free
About
This dataset features approximately 53,500 academic papers along with their associated metadata. It is designed to aid various natural language processing (NLP) tasks, such as classification and retrieval. The collection covers a broad spectrum of research fields, including computer science, biology, social sciences, and engineering. Each paper includes essential metadata such as the publish date, title, abstract, author(s), and category. The data is carefully assembled to ensure accuracy, making it a valuable resource for researchers and data enthusiasts keen on advancing NLP applications in academic domains.
Columns
- Index: A numerical identifier for each entry.
- id: The unique identifier for each paper.
- Title: The title of the academic article.
- Summary: A concise abstract of the article.
- Author: The primary author of the paper.
- Link: A direct link to download the PDF version of the paper.
- Publish Date: The date when the paper was initially published.
- Update Date: The date when the paper's information was last updated.
- Primary Category: The main arXiv category assigned to the paper.
- Category: Additional related categories for the paper.
Distribution
The dataset is typically provided in a CSV data file format. It comprises 53,500 individual samples or records, each representing an academic article with its corresponding metadata. The structure involves rows of data where each column provides specific details as listed above.
Usage
This dataset offers ideal applications for several academic and data science tasks:
- Document Classification: Create models to group academic papers into relevant research areas or topics.
- Document Retrieval: Develop effective search systems to quickly find pertinent papers based on user queries or keywords.
- Topic Modelling: Analyse the dataset to uncover significant topics or themes present within the academic literature.
- Recommendation Systems: Build personalised systems that suggest relevant papers to users based on their interests.
- Broader NLP applications such as sentiment analysis and keyword extraction.
Coverage
The dataset offers a global scope of academic papers. It covers a significant time range, with papers published from November 1988 through to August 2023. There are no specific demographic details provided for the authors or subjects, focusing primarily on the academic content itself.
License
CCO
Who Can Use It
This dataset is intended for researchers, data enthusiasts, and practitioners who are interested in developing and testing natural language processing models. It is particularly useful for those focusing on academic content organisation, information retrieval, and trend analysis within various scientific and social disciplines.
Dataset Name Suggestions
- Academic Papers Metadata Collection
- arXiv Scientific Articles Dataset
- NLP Research Papers
- Scholarly Article Data
- Global Academic NLP Dataset
Attributes
Original Data Source: Papers by Subject
QUALITY