关于DeepSeek的早期学术文献中的积极情绪:一个跨学科的迷你回顾
Yuxing He1, Angie Giangan2, Nam Vu3
1Faculty of Law, Bond University, Robina, QLD, Australia.
Frontiers in artificial intelligence
|January 28, 2026
概括
DeepSeek是一个免费的大型语言模型 (LLM),在计算机科学和工程等科学学科中得到了积极的评价. 学术文献显示出一种主要是积极的情绪,与早期的ChatGPT研究不同.
科学领域:
- 计算机科学 计算机科学
- 工程 工程师 工程师 工程师
- 医学 医学 医学 医学 医学
- 数学 数学 是一个数学.
- 商业 商业 商业 商业
- 环境科学 环境科学
背景情况:
- DeepSeek是一个被广泛下载的,免费的,自主托管的大型语言模型 (LLM).
- 早期关于ChatGPT等类似模型的学术文献往往是批判性的.
- 本研究探讨了各个学科对DeepSeek的学术接收和评估.
研究的目的:
- 分析有关DeepSeek的学术文献的情绪和学科分布.
- 为了比较DeepSeek的学术接待与ChatGPT的学术接待.
- 确定与DeepSeek相关的突出研究领域和主题.
主要方法:
- 在标题,摘要或关键字中提到DeepSeek的文章的文献评论.
- 由于跨语言的情感分析限制,中国文学被排除在外.
- 使用VADER (瓦伦西亚意识到词典和情绪推理器) 工具进行情感分析.
主要成果:
- 计算机科学,工程和医学是研究DeepSeek最活跃的领域.
- 总体而言,对DeepSeek的学术情绪是积极的,计算机科学显示了最高的积极情绪.
- 在分析的文献中,对DeepSeek的政治或伦理影响的讨论是有限的.
结论:
- 在科学界中,DeepSeek在很大程度上得到了积极的接待,与早期对ChatGPT的批评观点形成鲜明对比.
- 进一步的研究可以探索区域视角和更广泛的伦理考虑.
- 这项研究突出了对DeepSeek实际应用和性能的重大学术兴趣.
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