An experiential account of a large-scale interdisciplinary data analysis of public engagement1
Date
2022
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Article
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22 p.
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Abstract
This article presents our experience as a multidisciplinary team systematizing and analyzing the transcripts from the largest yet (1.775 conversations) series of conversations about Chile’s future. This project called “Tenemos Que Hablar de Chile” [We have to talk about Chile] gathered more than 8000 people from all municipalities, achieving gender, age, and educational parity. In this sense, this article takes an experiential approach to describe how certain interdisciplinary methodological decisions were made. We sought to apply analytical variables derived from social science theories and operationalize them through modern linguistics to guide a more theoretically-informed natural language processing. The analysis was divided into three stages: (1) a descriptive analysis adapting descriptions of computational grounded theory, (2) a futurization analysis operationalizing concepts from futures studies, and (3) an argumentative analysis operationalizing concepts from argumentation theory. Overall, our methodological experimentation shed light on potential learnings for integrating a multidisciplinary perspective on NLP analysis with sensitive social content. Firstly, we developed a strategy for translation of knowledge based on the construction of what we called "analytical categories” in which a normative expectation or descriptive dimension was identified in the body of literature, operationalized through linguistics, and programmed in Python or R. Ultimately, we seek to reflect on the importance interdisciplinarity not only as means to find new analysis ideas but rather, to incorporate the critical, political and epistemological points of view to understand analysis as complex socio-technical processes.
Description
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Citation
Goñi, Julian “Iñaki” ; Fuentes, Claudio & Raveau, Maria Paz (forthcoming). An experiential account of a large-scale interdisciplinary data analysis of public engagement. AI and Society:1-13.
Keywords
Natural Language Processing, Deliberation, Public Dialogue, Interdisciplinary research