Scientific articles play a crucial role in advancing knowledge and informing research directions. One key aspect of evaluating scientific articles is the analysis of citations, which provides insights into the impact and reception of the cited works. This article introduces the innovative use of large language models, particularly ChatGPT, for comprehensive sentiment analysis of citations within scientific articles. By leveraging advanced natural language processing (NLP) techniques, ChatGPT can discern the nuanced positivity or negativity of citations, offering insights into the reception and impact of cited works. Furthermore, ChatGPT's capabilities extend to detecting potential biases and conflicts of interest in citations, enhancing the objectivity and reliability of scientific literature evaluation. This study showcases the transformative potential of artificial intelligence (AI)-powered tools in enhancing citation analysis and promoting integrity in scholarly research.

翻译：科学文献在推动知识进步和引导研究方向中扮演关键角色。评估科学文献的一个核心环节是分析引文，这有助于揭示被引文献的影响力与接受程度。本文创新性地引入大型语言模型（尤其是ChatGPT），对科学文献中的引文进行全面的情感分析。通过利用先进的自然语言处理技术，ChatGPT能够辨别引文在情感上的细微积极或消极倾向，从而为被引文献的接受度与影响力提供深入见解。此外，ChatGPT的能力还延伸至检测引文中潜在的偏见与利益冲突，从而提升科学文献评估的客观性与可靠性。本研究展示了人工智能驱动工具在增强引文分析、促进学术研究诚信方面的变革潜力。