Word Counting Is Not Enough: A Syntax-Driven Computational Method for Analyzing Participation

Traditional methods of citizen deliberation, such as mini-publics, have been criticized for their limited scope. However, the implementation of massive deliberative processes creates new socio-technical challenges, particularly at the systematization stage. In general, the task of processing citizen participation is typically met with the general tools of textual analysis and Natural Language Processing (NLP). However, processing participation is not just a technical problem, but fundamentally a problem of normative design whose solution must be coherent with the philosophical, ethical, and institutional decisions that the participatory process embodies. In this article, we show how, using basic syntactic rules, we can produce simple and highly explainable reconstructions of public opinions. This methodology was tested on datasets from Chilean participatory processes, specifically dialogs from We have to talk about Chile and the 2023 Constituent Process. We show how our strategy enables further information extraction by identifying different syntactic components, providing deeper insights into the answers, while aligning with the goals of citizen participation. Overall, this study presents a compelling alternative for interpreting large volumes of citizen input, particularly in ways that preserve context and advance a more coherent analytical framework aligned with the normative ideals of deliberative democracy.