paper-with-me

홈 › Papers

Characterizing References from Different Disciplines: A Perspective of Citation Content Analysis

2021-01-19 · Chengzhi Zhang, Lifan Liu, Yuzhuo Wang

Multidisciplinary cooperation is now common in research since social issues inevitably involve multiple disciplines. In research articles, reference information, especially citation content, is an important representation of communication among different disciplines. Analyzing the distribution characteristics of references from different disciplines in research articles is basic to detecting the sources of referred information and identifying contributions of different disciplines. This work takes articles in PLoS as the data and characterizes the references from different disciplines based on Citation Content Analysis (CCA). First, we download 210,334 full-text articles from PLoS and collect the information of the in-text citations. Then, we identify the discipline of each reference in these academic articles. To characterize the distribution of these references, we analyze three characteristics, namely, the number of citations, the average cited intensity and the average citation length. Finally, we conclude that the distributions of references from different disciplines are significantly different. Although most references come from Natural Science, Humanities and Social Sciences play important roles in the Introduction and Background sections of the articles. Basic disciplines, such as Mathematics, mainly provide research methods in the articles in PLoS. Citations mentioned in the Results and Discussion sections of articles are mainly in-discipline citations, such as citations from Nursing and Medicine in PLoS.

📄 PDF Abstract BibTeX arXiv:2101.07614

Code (0)

등록된 구현이 없습니다.

Tasks

Articles

Similar Papers 제목 키워드 기반

Citcom – Citation Recommendation

2020-09-28 · NFORMATIK 2020 2020 9 · Melina Meyer, Jenny Frey, Tamino Laub, Marco Wrzalik 외

Citation recommendation aims to predict references based on a given text. In this paper, we focus on predicting references using small passages instead of a whole document. Besides using a search engine as baseline, we i…

Citation RecommendationFeature Engineering

When to Ask a Question: Understanding Communication Strategies in Generative AI Tools

2026-05-11 · Charlotte Park, Kate Donahue, Manish Raghavan arxiv

Generative AI models differ from traditional machine learning tools in that they allow users to provide as much or as little information as they choose in their inputs. This flexibility often leads users to omit certain …

Time to Cite: Modeling Citation Networks using the Dynamic Impact Single-Event Embedding Model

2024-02-28 · Nikolaos Nakis, Abdulkadir Celikkanat, Louis Boucherie, Sune Lehmann 외

Understanding the structure and dynamics of scientific research, i.e., the science of science (SciSci), has become an important area of research in order to address imminent questions including how scholars interact to a…

Network Embedding

SemanticCite: Citation Verification with AI-Powered Full-Text Analysis and Evidence-Based Reasoning

2025-11-20 · Sebastian Haan arxiv

Effective scientific communication depends on accurate citations that validate sources and guide readers to supporting evidence. Yet academic literature faces mounting challenges: semantic citation errors that misreprese…

ChatGPT cites the most-cited articles and journals, relying solely on Google Scholar's citation counts. As a result, AI may amplify the Matthew Effect in environmental science

2023-04-13 · Eduard Petiska

ChatGPT (GPT) has become one of the most talked-about innovations in recent years, with over 100 million users worldwide. However, there is still limited knowledge about the sources of information GPT utilizes. As a resu…

Articles