Alex J Yang
Biographic Data
| ID | 9458197 |
|---|---|
| NAME | Alex J Yang |
| GIVEN NAMES | Alex J |
| FAMILY NAME | Yang |
| SIGNATURE | YANG A J |
| AFFILIATIONS | Nanjing University |
| ORCID | 0000-0002-1276-0483 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Repeat collaboration and scientific innovation
This study explores how collaboration dynamics influence scientific innovation in Physics, Chemistry, and Physiology or Medicine by analyzing the evolving ego networks of Nobel laureates. Using data from the Microsoft Academic Graph and an updated Nobel laureate dataset (1900–2024), we quantify collaboration patterns through collaboration length and cumulative coauthorship strength within dynamic ego networks. Innovation is measured via four fiel…
Standing on the shoulder of data
Unveiling the dynamics of team age structure and its impact on scientific innovation
Rescaling the disruption index reveals the universality of disruption distributions in science
Dynamic patterns of the disruptive and consolidating knowledge flows in Nobel-winning scientific breakthroughs
Scientific breakthroughs possess the transformative potential to reshape research trajectories and scientific paradigms. However, there is limited systematic evidence on how these breakthroughs influence the evolution of scientific knowledge. Building on the concepts of disruption and consolidation in science, we categorize forward-citing papers into two distinct categories: Disruptive Citing Papers (DCP) and Consolidating Citing Papers (CCP). An…
Female-led teams produce more innovative ideas yet receive less scientific impact
Despite long-standing concerns about gender bias in science, there remains a lack of understanding regarding the performance of female scientists as team leaders compared to their male counterparts. This study explores differences between female-led and male-led teams in terms of scientific impact, novelty, and disruption, utilizing a comprehensive data set of journal articles spanning from 1980 to 2016 across STEM fields. We employed Coarsened E…
No prominent works on this page.
Unveiling the dynamics of team age structure and its impact on scientific innovation
Rescaling the disruption index reveals the universality of disruption distributions in science
Dynamic patterns of the disruptive and consolidating knowledge flows in Nobel-winning scientific breakthroughs
Scientific breakthroughs possess the transformative potential to reshape research trajectories and scientific paradigms. However, there is limited systematic evidence on how these breakthroughs influence the evolution of scientific knowledge. Building on the concepts of disruption and consolidation in science, we categorize forward-citing papers into two distinct categories: Disruptive Citing Papers (DCP) and Consolidating Citing Papers (CCP). An…
Female-led teams produce more innovative ideas yet receive less scientific impact
Despite long-standing concerns about gender bias in science, there remains a lack of understanding regarding the performance of female scientists as team leaders compared to their male counterparts. This study explores differences between female-led and male-led teams in terms of scientific impact, novelty, and disruption, utilizing a comprehensive data set of journal articles spanning from 1980 to 2016 across STEM fields. We employed Coarsened E…
Repeat collaboration and scientific innovation
This study explores how collaboration dynamics influence scientific innovation in Physics, Chemistry, and Physiology or Medicine by analyzing the evolving ego networks of Nobel laureates. Using data from the Microsoft Academic Graph and an updated Nobel laureate dataset (1900–2024), we quantify collaboration patterns through collaboration length and cumulative coauthorship strength within dynamic ego networks. Innovation is measured via four fiel…
Standing on the shoulder of data
scientometrics and bibliometrics research (5 works) · Computer Science (3 works) · Sociology (3 works) · Conferences and Exhibitions Management (2 works) · Data science (2 works) · Engineering (2 works) · Engineering ethics (2 works) · Psychology (2 works) · Sociology of scientific knowledge (2 works) · Transformative learning (2 works)