Open Collections

Bucci, Paul

University of British Columbia

How do we compute meaning? To make something computable, we must reduce the world to logical operations on electrical signals. However, our human experience is that the world has an uncomputable, meaningful aspect that seems to defy mere information processing. The quantitative world of computing demands measurable, objective signals to be translated into the qualitative world of affect, emotion, and meaning. Is it possible to make the two worlds of qualitative and quantitative meet? In this dissertation, I report on, analyze, and draw conclusions from two multi-part projects that attempt to answer this question from different perspectives using interactive systems and machine learning. First, we look at computing meaning by attempting to detect emotions using signals derived from the body such as heart rate, brain waves, and gestures. Then, we look at computing meaning by making connections between documents to support thematic exploration of large document corpora. My contributions in this dissertation are: A critical theoretical and methodological proposition for computationally representing, sensing, and displaying real-time emotions. A synthesis of the theoretical and pragmatic basis of therapeutic care methods and their meaning for affective robotics, with an accompanying account of the constructed nature of emotions for HRI applications. The design and evaluation of a system (called Teleoscope) for capturing underlying meaning in documents through interaction with machine learning systems. An extension to thematic analysis for data curation to create meaning in large text datasets, which we call thematic exploration, and a methodological concept of schema crystallization. Through these projects, an underlying understanding of meaning-making as an embedded, embodied, emergent, interactive phenomenon is articulated. That is to say, meaning is embedded in a culture and environment, embodied in the whole of a person, and emerges through the process of interaction between a person, themselves, other people, and their environment. By understanding these epiphenomenal interactions, designers may be enabled to create computational systems that facilitate richer meaning-making.

Text

2024-10-24

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/89487

Computer Science

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/