The presence of occupational structure in online texts based on word embedding NLP models
CSS-Recens Research Group, Centre for Social Sciences – Hungarian Academy of Sciences Centre of Excellence, Tóth Kálmán u. 4, 1097, Budapest, Hungary
2 Faculty of Social Sciences, Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117, Budapest, Hungary
3 Department of Network and Data Science, Central European University, A-1100, Vienna, Austria
Accepted: 15 November 2021
Published online: 27 November 2021
Research on social stratification is closely linked to analyzing the prestige associated with different occupations. This research focuses on the positions of occupations in the semantic space represented by large amounts of textual data. The results are compared to standard results in social stratification to see whether the classical results are reproduced and if additional insights can be gained into the social positions of occupations. The paper gives an affirmative answer to both questions.
The results show a fundamental similarity of the occupational structure obtained from text analysis to the structure described by prestige and social distance scales. While our research reinforces many theories and empirical findings of the traditional body of literature on social stratification and, in particular, occupational hierarchy, it pointed to the importance of a factor not discussed in the mainline of stratification literature so far: the power and organizational aspect.
Key words: Social stratification / Prestige / Occupations / Natural Language Processing / Word embedding / Text mining
© The Author(s) 2021
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