paper-with-me

Papers

Combining psychoanalysis and computer science: an empirical study of the relationship between emotions and the Lacanian discourses

2024-10-30 · Minas Gadalla, Sotiris Nikoletseas, José Roberto de A. Amazonas

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.

📄 PDF Abstract BibTeX arXiv:2410.22895

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Return to Lacan: an approach to digital twin mind with free energy principle

2023-09-13 · Lingyu Li, Chunbo Li

Free energy principle (FEP) is a burgeoning theory in theoretical neuroscience that provides a universal law for modelling living systems of any scale. Expecting a digital twin mind from this first principle, we propose …

Humanoid Artificial Consciousness Designed with Large Language Model Based on Psychoanalysis and Personality Theory

2025-10-10 · Sang Hun Kim, Jongmin Lee, Dongkyu Park, So Young Lee 외 arxiv

Human consciousness is still a concept hard to define with current scientific understanding. Although Large Language Models (LLMs) have recently demonstrated significant advancements across various domains including tran…

Concepts and Experiments on Psychoanalysis Driven Computing

2022-09-29 · Minas Gadalla, Sotiris Nikoletseas, José Roberto de A. Amazonas, José D. P. Rolim

This research investigates the effective incorporation of the human factor and user perception in text-based interactive media. In such contexts, the reliability of user texts is often compromised by behavioural and emot…

Fake News Detection

See Your Heart: Psychological states Interpretation through Visual Creations

2023-02-11 · Likun Yang, Xiaokun Feng, Xiaotang Chen, Shiyu Zhang 외

In psychoanalysis, generating interpretations to one's psychological state through visual creations is facing significant demands. The two main tasks of existing studies in the field of computer vision, sentiment/emotion…

Emotion ClassificationImage Captioning

A Chain-of-Thought Prompting Approach with LLMs for Evaluating Students' Formative Assessment Responses in Science

2024-03-21 · Clayton Cohn, Nicole Hutchins, Tuan Le, Gautam Biswas

This paper explores the use of large language models (LLMs) to score and explain short-answer assessments in K-12 science. While existing methods can score more structured math and computer science assessments, they ofte…

Active LearningMath