Huimin Xu

ORCID: 0000-0002-1918-7317
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About
Contact & Profiles
Research Areas
  • scientometrics and bibliometrics research
  • Crystallization and Solubility Studies
  • X-ray Diffraction in Crystallography
  • Team Dynamics and Performance
  • Innovation and Knowledge Management
  • Career Development and Diversity
  • Retirement, Disability, and Employment
  • Complex Network Analysis Techniques
  • Media, Gender, and Advertising
  • Work-Family Balance Challenges
  • Water Quality Monitoring Technologies
  • Geometric Analysis and Curvature Flows
  • Conferences and Exhibitions Management
  • Algebraic Geometry and Number Theory
  • Meta-analysis and systematic reviews
  • Diversity and Career in Medicine
  • Social Media and Politics
  • Opinion Dynamics and Social Influence
  • Gender Roles and Identity Studies
  • Grit, Self-Efficacy, and Motivation
  • COVID-19 epidemiological studies
  • Nonlinear Waves and Solitons
  • Media Influence and Health
  • Mental Health Research Topics
  • Gender, Feminism, and Media

The University of Texas at Austin
2022-2024

Nanjing University
2019

Harbin Normal University
2018

Our analysis of thousands movies and books reveals how these cultural products weave stereotypical gender roles into morality tales perpetuate inequality through storytelling. Using the word embedding techniques, we reveal constructed emotional dependency female characters on male in stories.

10.1371/journal.pone.0225385 article EN cc-by PLoS ONE 2019-11-22

Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable insights healthcare but resource-intensive. Large Language Models (LLMs) have been introduced to perform TA, yet their applications remain unexplored. Here, we propose TAMA: A Human-AI Collaborative Analysis framework using Multi-Agent LLMs clinical interviews. We leverage the scalability and coherence of multi-agent systems through structured...

10.48550/arxiv.2503.20666 preprint EN arXiv (Cornell University) 2025-03-26

Abstract Power dynamics influence every aspect of scientific collaboration. Team power can be measured by team level and hierarchy. is conceptualized as the average possession resources, expertise, or decision‐making authorities a team. hierarchy represents vertical differences possessions resources in In Science Science, few studies have looked at collaboration from perspective dynamics. This research examines how affect impact to fill gap. this research, all coauthors one publication are...

10.1002/asi.24653 article EN Journal of the Association for Information Science and Technology 2022-05-03

ABSTRACT The citation of scientific papers is considered a simple and direct indicator papers' impact. This paper predicts citations through team‐related variables, team composition, structure. Team composition includes size, male/female dominance, academia/industry collaboration, unique race number, country number. structures are made up power level hierarchy. members' previous H‐index, collaborators, career age, numbers proxy power. We calculated the mean value Gini coefficient to...

10.1002/pra2.804 article EN Proceedings of the Association for Information Science and Technology 2023-10-01

In this paper, by introducing a new frame on spacelike curves lying in lightcone 3‐space, we investigate the geometric properties of lightlike surface Darboux‐like indicatrix and binormal generated 3‐space. As an extension our previous work application singularity theory, singularities surfaces are classified, several invariants discovered to be useful for characterizing these singularities, meanwhile, it is found that also measure order contact between or principal normal indicatrixes...

10.1002/mma.5199 article EN Mathematical Methods in the Applied Sciences 2018-08-19

Accompanied by the development of digital media, threat information cocoon has become a significant issue. However, little is known about measure as cultural space and its relationship with social class. This study addresses this problem constructing word embedding models random shuffling methods among three large-scale media use datasets. In light field theory production, we investigate effect on different classes 979 computer users, 100,000 smartphone 159,373 mobile reading application...

10.48550/arxiv.2007.10083 preprint EN other-oa arXiv (Cornell University) 2020-01-01

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10.2139/ssrn.4751297 preprint EN 2024-01-01

The dropout of scholars not only results in the potential loss valuable resources but also poses setbacks for scientific community. However, existing knowledge on this phenomenon has been limited to a few fields, lacking consistency across career status and neglecting its dynamic nature. To address gap, we reconstructed trajectories over 24 million 19 fields from MAG dataset examined rates at three levels: field, status, generation. Our findings indicate that women exhibit significantly...

10.2139/ssrn.4800776 preprint EN 2024-01-01

The Bridge2AI project, funded by the National Institutes of Health, involves researchers from different disciplines and backgrounds to develop well-curated AI health data tools. Understanding cross-disciplinary cross-organizational collaboration at individual, team, project levels is critical. In this paper, we matched team members PubMed Knowledge dataset get their health-related publications. We built network for all collaborators sorted out with largest degree centrality betweenness...

10.1145/3543873.3587579 article EN cc-by 2023-04-28
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