Measuring populist discourse with semantic text analysis: an application on grassroots populist mobilization. Aslanidis, P. Quality & Quantity, 52(3):1241–1263, May, 2018. ![Measuring populist discourse with semantic text analysis: an application on grassroots populist mobilization [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Populism is a concept employed to qualify the political behavior of a large number of actors at a worldwide scale, with scientists classifying the latter into populists and non-populists according to dimensions such as ideology, strategy, discourse, economic policy, and even style. This article analyzes existing schools of thought on the nature of populism and argues that conceptualizing populism as a specific type of anti-elite discourse in the name of the People is both conceptually and methodologically the most coherent and useful way to understand the phenomenon. Additionally, it suggests discarding crude, dichotomous classification in favor of a gradated view of populist mobilization by means of quantifying populist discourse and observing its spatial and temporal variation. It adds value to current methods of measurement by demonstrating why and how clause-based semantic text analysis can provide optimal quantitative results while retaining qualitative elements for mixed-methods analysis. Aiming, moreover, at expanding the scope of populism studies by overcoming a narrow view that focuses exclusively at party system developments, it applies semantic text analysis to the study of grassroots mobilization during the Great Recession. Results point to the wide use of populist discourse on the part of movement activists seeking an inclusive language when framing disparate social grievances in a given constituency, a finding with important implications with regards to how populism can facilitate straddling the divide that purportedly distinguishes institutionalized party system behavior from the social movement milieu.
@article{aslanidis_measuring_2018,
title = {Measuring populist discourse with semantic text analysis: an application on grassroots populist mobilization},
volume = {52},
issn = {1573-7845},
shorttitle = {Measuring populist discourse with semantic text analysis},
url = {https://doi.org/10.1007/s11135-017-0517-4},
doi = {10.1007/s11135-017-0517-4},
abstract = {Populism is a concept employed to qualify the political behavior of a large number of actors at a worldwide scale, with scientists classifying the latter into populists and non-populists according to dimensions such as ideology, strategy, discourse, economic policy, and even style. This article analyzes existing schools of thought on the nature of populism and argues that conceptualizing populism as a specific type of anti-elite discourse in the name of the People is both conceptually and methodologically the most coherent and useful way to understand the phenomenon. Additionally, it suggests discarding crude, dichotomous classification in favor of a gradated view of populist mobilization by means of quantifying populist discourse and observing its spatial and temporal variation. It adds value to current methods of measurement by demonstrating why and how clause-based semantic text analysis can provide optimal quantitative results while retaining qualitative elements for mixed-methods analysis. Aiming, moreover, at expanding the scope of populism studies by overcoming a narrow view that focuses exclusively at party system developments, it applies semantic text analysis to the study of grassroots mobilization during the Great Recession. Results point to the wide use of populist discourse on the part of movement activists seeking an inclusive language when framing disparate social grievances in a given constituency, a finding with important implications with regards to how populism can facilitate straddling the divide that purportedly distinguishes institutionalized party system behavior from the social movement milieu.},
language = {en},
number = {3},
urldate = {2021-12-16},
journal = {Quality \& Quantity},
author = {Aslanidis, Paris},
month = may,
year = {2018},
pages = {1241--1263},
}
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