Facilitating Opinion Diversity through Hybrid NLP Approaches

TL;DR

This thesis proposes a three-layered hierarchy for representing perspectives that can be obtained by a mixture of human intelligence and large language models and illustrates how these representations can draw insights into the diversity of perspectives and allow us to investigate interactions in online discussions.

Abstract

Modern democracies face a critical issue of declining citizen participation in decision-making. Online discussion forums are an important avenue for enhancing citizen participation. This thesis proposal 1) identifies the challenges involved in facilitating large-scale online discussions with Natural Language Processing (NLP), 2) suggests solutions to these challenges by incorporating hybrid human-AI technologies, and 3) investigates what these technologies can reveal about individual perspectives in online discussions. We propose a three-layered hierarchy for representing perspectives that can be obtained by a mixture of human intelligence and large language models. We illustrate how these representations can draw insights into the diversity of perspectives and allow us to investigate interactions in online discussions.

Figures (2)

• Figure 1: Feedback loops in Hybrid Intelligence.
• Figure 2: The perspective hierarchy. The higher the level of abstraction, the more human intelligence is required for interpreting the component.