Chengzhi Zhang

This paper investigates the distribution and evolution of aspect-level sentiments in peer review comments of accepted papers from Nature Communications, revealing a consistent trend of increasing positive sentiments and decreasing negative sentiments as the number of review rounds increases.

This study constructs and analyzes large-scale algorithm co-occurrence networks in natural language processing using deep learning models.

This paper investigates the correlation between gender diversity and the scientific impact of papers in Natural Language Processing (NLP) and Library and Information Science (LIS) domains.