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.

翻译：本研究探讨精神分析与计算机科学之间的跨学科互动，提出两者之间存在互利互惠的交流。事实上，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。反之，计算机科学，特别是人工智能（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感线索。本研究特别致力于运用计算机科学方法，建立情感与拉康话语之间的基本关系。这些关系通过我们的实证研究与统计分析得以发现，并最终以理论（精神分析）方式加以验证。值得注意的是，尽管情感在拉康理论中已有零星研究，但据我们所知，目前仍缺乏对其作用的系统性、细致化探讨。这种对情感作用的精细理解，亦可使拉康话语的识别在实践中更为高效便捷。具体而言，我们的方法揭示了在对应话语方面具有最高区分力的情感；反之，我们为每种话语识别出其最具特征性的情感。事实上，我们开发了一种称为拉康话语发现（LDD）的方法，该方法通过系统化过程简化了文本中拉康话语的识别。尽管本文的主要贡献本质上是理论性（精神分析）的，但它也能促进交互式数字系统领域的重大实际应用。事实上，我们的方法可通过人工智能技术实现自动化，有效识别文本中的情感（及对应话语）。