TL;DR
This paper proposes a hybrid human-AI NLP framework to enhance and analyze opinion diversity in online discussions, aiming to improve citizen participation in democratic decision-making.
Contribution
It introduces a three-layered hierarchy for representing perspectives using combined human and large language model insights, addressing challenges in large-scale online discussion analysis.
Findings
A new perspective representation hierarchy is proposed.
Hybrid approaches reveal insights into opinion diversity.
Potential to improve online democratic engagement.
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.
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