精神分析与计算机科学的结合：情绪与拉康话语关系的实证研究
Combining psychoanalysis and computer science: an empirical study of the relationship between emotions and the Lacanian discourses
AI总结：
本研究跨学科结合精神分析与计算机科学，提出LDD方法，通过实证与统计分析建立情绪与拉康话语的关联并验证，填补相关研究空白，兼具理论价值与数字系统应用潜力。
摘要：
本研究探索了精神分析与计算机科学之间的跨学科互动，提出二者可实现互利共赢。一方面，精神分析概念能够丰富涉及人类因素中无意识、难以捉摸层面的技术应用，例如社交媒体及其他交互式数字平台。另一方面，计算机科学，尤其是人工智能（AI），可为精神分析提供量化概念与方法，识别人类表达中的模式与情绪线索。具体而言，本研究旨在运用计算机科学方法，建立情绪与拉康话语（Lacanian discourses）之间的基础关联。我们的研究路径通过实证调查与统计分析发现此类关联，并最终通过理论（精神分析）方式加以验证。值得注意的是，尽管拉康理论中已有对情绪的零散研究，但据我们所知，目前仍缺乏对情绪作用的系统性、细致化探究。对情绪作用的这种精细化理解，也能让拉康话语的识别在实践中更高效、更简便。具体来说，我们的方法指出了在对应话语层面区分度最高的情绪；反过来，我们也识别出每种话语所包含的最具代表性的情绪。事实上，我们开发了一种名为拉康话语发现（Lacanian Discourse Discovery, LDD）的方法，该方法通过系统化流程简化了文本中拉康话语的识别工作。虽然本文的主要贡献本质上是理论性的（精神分析领域），但它也能推动交互式数字系统领域的重要实际应用。实际上，我们的方法可通过人工智能方法实现自动化，高效识别文本中的情绪（及对应话语）。
英文摘要：
This research explores the interdisciplinary interaction between psychoanalysis and computer science, suggesting a mutually beneficial exchange. Indeed, psychoanalytic concepts can enrich technological applications involving unconscious, elusive aspects of the human factor, such as social media and other interactive digital platforms. Conversely, computer science, especially Artificial Intelligence (AI), can contribute quantitative concepts and methods to psychoanalysis, identifying patterns and emotional cues in human expression. In particular, this research aims to apply computer science methods to establish fundamental relationships between emotions and Lacanian discourses. Such relations are discovered in our approach via empirical investigation and statistical analysis, and are eventually validated in a theoretical (psychoanalytic) way. It is worth noting that, although emotions have been sporadically studied in Lacanian theory, to the best of our knowledge a systematic, detailed investigation of their role is missing. Such fine-grained understanding of the role of emotions can also make the identification of Lacanian discourses more effective and easy in practise. In particular, our methods indicate the emotions with highest differentiation power in terms of corresponding discourses; conversely, we identify for each discourse the most characteristic emotions it admits. As a matter of fact, we develop a method which we call Lacanian Discourse Discovery (LDD), that simplifies (via systematizing) the identification of Lacanian discourses in texts. Although the main contribution of this paper is inherently theoretical (psychoanalytic), it can also facilitate major practical applications in the realm of interactive digital systems. Indeed, our approach can be automated through Artificial Intelligence methods that effectively identify emotions (and corresponding discourses) in texts.
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。
