SciEvo: A 2 Million, 30-Year Cross-disciplinary Dataset for Temporal Scientometric Analysis
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Abstract (arXiv)
Understanding the creation, evolution, and dissemination of scientific knowledge is crucial for bridging diverse subject areas and addressing complex global challenges such as pandemics, climate change, and ethical AI. Scientometrics, the quantitative and qualitative study of scientific literature, provides valuable insights into these processes. We introduce SciEvo, a longitudinal scientometric dataset with over two million academic publications, providing comprehensive contents information and citation graphs to support cross-disciplinary analyses. SciEvo is easy to use and available across platforms, including GitHub, Kaggle, and HuggingFace. Using SciEvo, we conduct a temporal study spanning over 30 years to explore key questions in scientometrics: the evolution of academic terminology, citation patterns, and interdisciplinary knowledge exchange. Our findings reveal critical insights, such as disparities in epistemic cultures, knowledge production modes, and citation practices. For example, rapidly developing, application-driven fields like LLMs exhibit significantly shorter citation age (2.48 years) compared to traditional theoretical disciplines like oral history (9.71 years). Our data and analytic tools can be accessed at https://github.com/Ahren09/SciEvo.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 21 of its 57 references that are in the map. First posted on arXiv 12 Oct 2024.
Builds on
21 of 57 references.
References · 21
- 2023GPT-4 Technical Reportcited by 18,396
- 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
- 2016Diachronic Word Embeddings Reveal Statistical Laws of Semantic Changecited by 221
- 2023Can large language models provide useful feedback on research papers? A large-scale empirical analysiscited by 200
- 2024AutoSurvey: Large Language Models Can Automatically Write Surveyscited by 119
- 2021Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Researchcited by 102
- 2024AgentReview: Exploring Peer Review Dynamics with LLM Agentscited by 93
- 2024When Search Engine Services meet Large Language Models: Visions and Challengescited by 59
- 2023unarXive 2022: All arXiv Publications Pre-Processed for NLP, Including Structured Full-Text and Citation Networkcited by 24
- 2022Investigating Fairness Disparities in Peer Review: A Language Model Enhanced Approachcited by 23
- 2021SciXGen: A Scientific Paper Dataset for Context-Aware Text Generationcited by 22
- 2015Homophily and missing links in citation networkscited by 21
9 more
- 2023We are Who We Cite: Bridges of Influence Between Natural Language Processing and Other Academic Fieldscited by 20
- 2023Predicting Information Pathways Across Online Communitiescited by 15
- 2023Forgotten Knowledge: Examining the Citational Amnesia in NLPcited by 13
- 2024Empowering Interdisciplinary Insights with Dynamic Graph Embedding Trajectoriescited by 3
- 2017Determining sentiment in citation text and analyzing its impact on the proposed ranking indexcited by 2
- 2017Unsupervised Extraction of Representative Concepts from Scientific Literaturecited by 2
- 2024Past, Present, and Future of Citation Practices in HCIcited by 2
- 2017Recency Bias in the Era of Big Data: The Need to Strengthen the Status of History of Mathematics in Nigerian Schoolscited by 1
- 2024Is there really a Citation Age Bias in NLP?cited by 1
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Citing papers per year: 2026: 2.
2 papers.