Yi Bu
Biographic Data
| ID | 6265917 |
|---|---|
| NAME | Yi Bu |
| GIVEN NAMES | Yi |
| FAMILY NAME | Bu |
| SIGNATURE | BU Y |
| AFFILIATIONS | Peking University |
| ORCID | 0000-0003-1737-3252 |
| VERIFIED | Yes |
| TOTAL WORKS | 17 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 17 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Has China caught up to the U.S. in AI research? An exploration of mimetic isomorphism as a model for late industrializers
Artificial intelligence represents a twenty-first century critical technology. We test for and find rapid learning and differentiation characterizing China’s AI development process as a model with a better fit than the Foreign Direct Investment/export-oriented growth of earlier Asian industrializers. China outproduces the U.S.A in both annual and cumulative numbers of AI papers, but quality measures show China lagging the U.S.; even so, China’s A…
Hot streaks and disruptiveness in the career of scientists
The creative output of scientists may be very different: Some papers may have a disruptive impact on science, some may consolidate existing knowledge, some may be highly influential, and others may yet have untapped potential (“sleeping beauty”). Unlike some previous studies that have explored the relationship between the impact and disruptiveness of papers, this study examines the disruptiveness of research during high impact periods (i.e., “hot…
Political hegemony, imitation isomorphism, and project familiarity
This paper contributes a new idea for exploring research funding effects on scholar performance. By collecting details of 9,501 research grants received by principal investigators from universities in U.S. social sciences from 2000 to 2019 and data on their publications and citations in the Microsoft Academic Graph and Web of Science bibliographic collections, we build a novel data set of grants and article counts, citations, and journal CiteScor…
Transforming role classification in scientific teams using LLMs and advanced predictive analytics
Scientific team dynamics are critical in determining the nature and impact of research outputs. However, existing methods for classifying author roles based on self-reports and clustering lack comprehensive contextual analysis of contributions. Thus, we present a transformative approach to classifying author roles in scientific teams using advanced large language models (LLMs), which offers a more refined analysis compared to traditional clusteri…
Consumer alternative protein choice in climate change
Interdisciplinary research attracts greater attention from policy documents
Interdisciplinary research is increasingly recognized as one of the solutions to today’s challenging scientific and societal issues. Many studies have aimed to explore the relationship between the interdisciplinarity of research and the attention they receive from the scientific community as well as society. However, the relationship between interdisciplinarity and attention from policy documents remains unclear. In this study, we utilize publica…
Analyzing research diversity of scholars based on multi-dimensional calculation of knowledge entities
Female early-career scientists have conducted less interdisciplinary research in the past six decades
Interdisciplinary research is a driving force of transformative and innovative science, yet it remains unclear how early-career scientists pursue interdisciplinary research paths. Analyzing data from 675,135 doctoral theses of U.S. Ph.D. graduates who graduated from 1950 to 2016, we study the development of interdisciplinary doctoral theses in the five scientific domains of behavioral sciences, biological sciences, engineering, health and medical…
Reply to issues about entitymetrics and paper-entity citation network
Encoding the citation life-cycle
Analyzing knowledge entities about Covid-19 using entitymetrics
COVID-19 cases have surpassed the 109 + million markers, with deaths tallying up to 2.4 million. Tens of thousands of papers regarding COVID-19 have been published along with countless bibliometric analyses done on COVID-19 literature. Despite this, none of the analyses have focused on domain entities occurring in scientific publications. However, analysis of these bio-entities and the relations among them, a strategy called entity metrics, could…
Revisiting the relationship between downloads and citations
An empirical review of the different variants of the probabilistic affinity index as applied to scientific collaboration
Predicting scientific breakthroughs based on knowledge structure variations
A multidimensional framework for characterizing the citation impact of scientific publications
The citation impact of a scientific publication is usually seen as a one-dimensional concept. We introduce a multidimensional framework for characterizing the citation impact of a publication. In addition to the level of citation impact, quantified by the number of citations received by a publication, we also conceptualize and operationalize the depth and breadth and the dependence and independence of the citation impact of a publication. The pro…
Keyword-citation-keyword network
Improving the Named Entity Recognition of Chinese Electronic Medical Records by Combining Domain Dictionary and Rules
Electronic medical records are an integral part of medical texts. Entity recognition of electronic medical records has triggered many studies that propose many entity extraction methods. In this paper, an entity extraction model is proposed to extract entities from Chinese Electronic Medical Records (CEMR). In the input layer of the model, we use word embedding and dictionary features embedding as input vectors, where word embedding consists of a…
Keyword-citation-keyword network
Improving the Named Entity Recognition of Chinese Electronic Medical Records by Combining Domain Dictionary and Rules
Electronic medical records are an integral part of medical texts. Entity recognition of electronic medical records has triggered many studies that propose many entity extraction methods. In this paper, an entity extraction model is proposed to extract entities from Chinese Electronic Medical Records (CEMR). In the input layer of the model, we use word embedding and dictionary features embedding as input vectors, where word embedding consists of a…
Analyzing knowledge entities about Covid-19 using entitymetrics
COVID-19 cases have surpassed the 109 + million markers, with deaths tallying up to 2.4 million. Tens of thousands of papers regarding COVID-19 have been published along with countless bibliometric analyses done on COVID-19 literature. Despite this, none of the analyses have focused on domain entities occurring in scientific publications. However, analysis of these bio-entities and the relations among them, a strategy called entity metrics, could…
Revisiting the relationship between downloads and citations
An empirical review of the different variants of the probabilistic affinity index as applied to scientific collaboration
Predicting scientific breakthroughs based on knowledge structure variations
A multidimensional framework for characterizing the citation impact of scientific publications
The citation impact of a scientific publication is usually seen as a one-dimensional concept. We introduce a multidimensional framework for characterizing the citation impact of a publication. In addition to the level of citation impact, quantified by the number of citations received by a publication, we also conceptualize and operationalize the depth and breadth and the dependence and independence of the citation impact of a publication. The pro…
Reply to issues about entitymetrics and paper-entity citation network
Encoding the citation life-cycle
Female early-career scientists have conducted less interdisciplinary research in the past six decades
Interdisciplinary research is a driving force of transformative and innovative science, yet it remains unclear how early-career scientists pursue interdisciplinary research paths. Analyzing data from 675,135 doctoral theses of U.S. Ph.D. graduates who graduated from 1950 to 2016, we study the development of interdisciplinary doctoral theses in the five scientific domains of behavioral sciences, biological sciences, engineering, health and medical…
Interdisciplinary research attracts greater attention from policy documents
Interdisciplinary research is increasingly recognized as one of the solutions to today’s challenging scientific and societal issues. Many studies have aimed to explore the relationship between the interdisciplinarity of research and the attention they receive from the scientific community as well as society. However, the relationship between interdisciplinarity and attention from policy documents remains unclear. In this study, we utilize publica…
Analyzing research diversity of scholars based on multi-dimensional calculation of knowledge entities
Hot streaks and disruptiveness in the career of scientists
The creative output of scientists may be very different: Some papers may have a disruptive impact on science, some may consolidate existing knowledge, some may be highly influential, and others may yet have untapped potential (“sleeping beauty”). Unlike some previous studies that have explored the relationship between the impact and disruptiveness of papers, this study examines the disruptiveness of research during high impact periods (i.e., “hot…
Political hegemony, imitation isomorphism, and project familiarity
This paper contributes a new idea for exploring research funding effects on scholar performance. By collecting details of 9,501 research grants received by principal investigators from universities in U.S. social sciences from 2000 to 2019 and data on their publications and citations in the Microsoft Academic Graph and Web of Science bibliographic collections, we build a novel data set of grants and article counts, citations, and journal CiteScor…
Transforming role classification in scientific teams using LLMs and advanced predictive analytics
Scientific team dynamics are critical in determining the nature and impact of research outputs. However, existing methods for classifying author roles based on self-reports and clustering lack comprehensive contextual analysis of contributions. Thus, we present a transformative approach to classifying author roles in scientific teams using advanced large language models (LLMs), which offers a more refined analysis compared to traditional clusteri…
Consumer alternative protein choice in climate change
Has China caught up to the U.S. in AI research? An exploration of mimetic isomorphism as a model for late industrializers
Artificial intelligence represents a twenty-first century critical technology. We test for and find rapid learning and differentiation characterizing China’s AI development process as a model with a better fit than the Foreign Direct Investment/export-oriented growth of earlier Asian industrializers. China outproduces the U.S.A in both annual and cumulative numbers of AI papers, but quality measures show China lagging the U.S.; even so, China’s A…
Computer Science (13 works) · Data science (10 works) · scientometrics and bibliometrics research (9 works) · Artificial Intelligence (7 works) · Epistemology (7 works) · Psychology (7 works) · Citation (6 works) · Political science (6 works) · Information retrieval (5 works) · Artificial Intelligence (4 works)