{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T02:05:01Z","timestamp":1787018701555,"version":"build-2736575974"},"reference-count":32,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2019,9,4]],"date-time":"2019-09-04T00:00:00Z","timestamp":1567555200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Information Science"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:p>This article proposes an automated methodology for the analysis of online political discourse. Drawing from the discourse quality index (DQI) by Steenbergen et al., it applies a machine learning\u2013based quantitative approach to measuring the discourse quality of political discussions online. The DelibAnalysis framework aims to provide an accessible, replicable methodology for the measurement of discourse quality that is both platform and language agnostic. The framework uses a simplified version of the DQI to train a classifier, which can then be used to predict the discourse quality of any non-coded comment in a given political discussion online. The objective of this research is to provide a systematic framework for the automated discourse quality analysis of large datasets and, in applying this framework, to yield insight into the structure and features of political discussions online.<\/jats:p>","DOI":"10.1177\/0165551519871828","type":"journal-article","created":{"date-parts":[[2019,9,4]],"date-time":"2019-09-04T03:17:26Z","timestamp":1567567046000},"page":"810-822","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["DelibAnalysis: Understanding the quality of online political discourse with machine learning"],"prefix":"10.1177","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7065-8006","authenticated-orcid":false,"given":"Eleonore","family":"Fournier-Tombs","sequence":"first","affiliation":[{"name":"School of Information Studies, McGill University, Canada"},{"name":"Institute of Information Service Science, University of 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