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：科学论文在推动知识进步和指导研究方向中发挥着关键作用。评估科学论文的一个重要方面是引文分析，这有助于了解被引文献的影响力和接受程度。本文创新性地引入大型语言模型（特别是ChatGPT）对科学论文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能够辨别引文的细微正面或负面情感，从而揭示被引文献的接受程度与影响力。此外，ChatGPT的能力还可扩展至检测引文中潜在的偏见与利益冲突，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及促进学术研究诚信方面的变革潜力。