Journal of Informetrics
ISSN: 1751-1577
Datasets associated with articles published in Journal of Informetrics
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- Data for: Understanding the Hierarchical Structural Evolution in a Scientific Discipline: An Artificial Intelligence Perspective65,887 AI-related research papers published during a 10-year period from 2009 to 2018.
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- Data for: Identification of highly-cited papers using topic-model-based and bibliometric features: the consideration of keyword popularityprediction of highly-cited papers in marketing and MIS
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- Data for: Analyzing Linguistic Complexity and Scientific Impact by Using Null ModelsDatase used in 'Analyzing Linguistic Complexity and Scientific Impact'.
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- Data for: Count Citations by Section? Introduction, Background, Methods, Discussion, Results and ConclusionsData behind Figures 1 to 8
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- FWCI and RCR comparison datasetThis is the dataset belonging to the article "Comparison of two article-level, field-independent citation metrics: Field-Weighted Citation Impact (FWCI) and Relative Citation Ratio (RCR)"
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- Data for: Does deep learning help topic extraction? A kernel k-means clustering method with word embeddingThe 4770 dataset includes 4770 articles in the Web of Science database, covering 10 disciplines, such as artificial intelligence, business, history, and chemistry. The 577 dataset includes 577 proposals granted by the National Science Foundation of the United States, and all the 577 proposals are within the area of computer science but are in different sub areas of computer science. The 6767 dataset includes 6767 articles published in Journal of the Association for Information Science and Technology, Journal of Informetrics, and Scientometrics from 2000 to 2016. No labels are given for this dataset.
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- Data for: Evidence of Open Access of scientific publications in Google Scholar: a large-scale analysisComplementary materials contain the annexes to the article, the raw data, and the data that resulted from the analysis
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- Data for: Which Western Higher Educational Institutions Join ResearchGate and what Affects their RG Scores?Data on European and US higher education institutions that have been used for the analyses presented in the paper.
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- Data for: Author Ranking Evaluation at ScaleThis data consists of two test data sets of researchers that have (1) received one or more prestigious prizes for the long-lasting and high impact contribution to their fields (596 data entries) and (2) author names of ACM fellows (1000 data entries). Each author in the data sets is matched to the corresponding ACM author profileID and multiple Microsoft Academic Graph author entity IDs (name disambiguated). It also includes citation counts, publication counts, download counts from various sources (ACM Digital Library, Google Scholar, Microsoft Academic).
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- Data for: How to Evaluate Rankings of Academic Entities using Test DataThis data consists of four test data sets consisting of academic entities (authors and papers) that have won various awards. Ranks of various ranking algorithms are given for each entity computed on two publication databases (Microsoft Academic Graph and ACM Digital Library). Test data sets: (1) acm fellows, (2) long time contribution awards for researchers, (3) best paper awards, and (4) high-impact papers.
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