用于生成电影评论的LLM评估：GPT-4o、Gemini-2.0和DeepSeek-V3
An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3
AI总结：
本研究提出使用GPT-4o、DeepSeek-V3和Gemini-2.0生成电影评论的框架，发现LLMs能生成结构完整的评论，其中DeepSeek-V3表现最均衡，与IMDb用户评论高度匹配，但在情感丰富度与风格连贯性上仍有待提升。
摘要：
大型语言模型（LLMs）在文本生成和摘要等各种任务中表现突出。LLMs在产品评论生成方面的适用性正获得越来越多的关注，为电影评论的生成铺平了道路。在本研究中，我们提出了一个使用三个LLMs（GPT-4o、DeepSeek-V3和Gemini-2.0）生成电影评论的框架，并通过将生成的输出与IMDb用户评论进行比较来评估它们的性能。我们使用电影字幕和剧本作为LLMs的输入，并研究它们如何影响生成评论的质量。我们从词汇、情感极性、相似性和主题一致性方面对基于LLM的电影评论进行了审查，并与IMDB用户评论进行了比较。结果表明，LLMs能够生成句法流畅且结构完整的电影评论。然而，LLM生成的评论与IMDb评论之间在情感丰富度和风格连贯性上仍存在明显差距，这表明需要进一步改进以提升电影评论生成的整体质量。我们提供了一项基于调查的分析，要求参与者区分LLM评论和IMDb用户评论。结果显示，LLM生成的评论很难与IMDB用户评论区分开来。我们发现DeepSeek-V3生成的评论最为均衡，与IMDb评论高度匹配。GPT-4o过度强调积极情感，而Gemini-2.0更好地捕捉了消极情感，但表现出过度的情感强度。
英文摘要：
Large language models (LLMs) have been prominent in various tasks, including text generation and summarisation. The applicability of LLMs to the generation of product reviews is gaining momentum, paving the way for the generation of movie reviews. In this study, we propose a framework that generates movie reviews using three LLMs (GPT-4o, DeepSeek-V3, and Gemini-2.0), and evaluate their performance by comparing the generated outputs with IMDb user reviews. We use movie subtitles and screenplays as input to the LLMs and investigate how they affect the quality of reviews generated. We review the LLM-based movie reviews in terms of vocabulary, sentiment polarity, similarity, and thematic consistency in comparison to IMDB user reviews. The results demonstrate that LLMs are capable of generating syntactically fluent and structurally complete movie reviews. Nevertheless, there is still a noticeable gap in emotional richness and stylistic coherence between LLM-generated and IMDb reviews, suggesting that further refinement is needed to improve the overall quality of movie review generation. We provided a survey-based analysis where participants were told to distinguish between LLM and IMDb user reviews. The results show that LLM-generated reviews are difficult to distinguish from IMDB user reviews. We found that DeepSeek-V3 produced the most balanced reviews, closely matching IMDb reviews. GPT-4o overemphasised positive emotions, while Gemini-2.0 captured negative emotions better but showed excessive emotional intensity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
