The concept that went viral: Using machine learning to discover charisma in the wild

The term "charisma" is recognized as sociology's most successful export to common speech. While sociologists habitually dismiss popular uses of the word, we address its vernacularity head on as a worthy object of study and as a potential resource for conceptual development. Using machine learning, we locate "charisma" within the wider discursive field out of which it arises (and continues to arise) across four corpora; namely: Weber's major writings; social scientific research (123,531 JSTOR articles); and social media ("X") posts containing of "charisma" (n=77,161) and its 2023 variant, "rizz" (n=85,869). By capturing meaning structures that discursively suspend "charisma" across multiple dimensions, we discern three spectra that help to distinguish charisma's sociological and non-sociological uses. Spectrum one differentiates perspectives which see charisma as having either a structural or individual-level range of efficacy. Spectrum two differentiates indifferent/analytical perspectives on charisma from perspectives which see it as desirable but also morally conservative. Spectrum three differentiates between relational and individualized ontologies for charisma. We find that, rather than hewing closely to the Weberian formulation, social scientific uses exist in an intermediate position vis-à-vis these three spectra. Thus, scholars participate in what they otherwise criticize as charisma's vulgarization. The article concludes with recommendations for how to constructively interact with 'popular charisma.'

Authors

Institutions

Publication Details

Journal
British Journal of Sociology
Published
2024-09-14
DOI
https://doi.org/10.1111/1468-4446.13146
Citations
1
Primary Topic
Social and Cultural Dynamics
Type
article
Field-Weighted Citation Impact
1.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The concept that went viral: Using machine learning to discover charisma in the wild

Paul Joosse, Yulin Lu
1 citations
British Journal of Sociology
Social and Cultural Dynamics
1.13
article

The concept that went viral: Using machine learning to discover charisma in the wild

Paul Joosse, Yulin Lu
article en
1 citations

Abstract

The term "charisma" is recognized as sociology's most successful export to common speech. While sociologists habitually dismiss popular uses of the word, we address its vernacularity head on as a worthy object of study and as a potential resource for conceptual development. Using machine learning, we locate "charisma" within the wider discursive field out of which it arises (and continues to arise) across four corpora; namely: Weber's major writings; social scientific research (123,531 JSTOR articles); and social media ("X") posts containing of "charisma" (n=77,161) and its 2023 variant, "rizz" (n=85,869). By capturing meaning structures that discursively suspend "charisma" across multiple dimensions, we discern three spectra that help to distinguish charisma's sociological and non-sociological uses. Spectrum one differentiates perspectives which see charisma as having either a structural or individual-level range of efficacy. Spectrum two differentiates indifferent/analytical perspectives on charisma from perspectives which see it as desirable but also morally conservative. Spectrum three differentiates between relational and individualized ontologies for charisma. We find that, rather than hewing closely to the Weberian formulation, social scientific uses exist in an intermediate position vis-à-vis these three spectra. Thus, scholars participate in what they otherwise criticize as charisma's vulgarization. The article concludes with recommendations for how to constructively interact with 'popular charisma.'

British Journal of SociologyVol. 76(1)
Lund University (SE), University of Hong Kong (HK)
Openalex Percentile: Top 17%
Social and Cultural Dynamics
1.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

The concept that went viral: Using machine learning to discover charisma in the wild — Paul Joosse, Yulin Lu · British Journal of Sociology (2024) | TGRS Research Map | TGRS