Cikkismertetés: Depressziós fórumok témáinak automatizált szövegelemzése a depresszió biopszichoszociális modelljének tükrében

Eszter Katona,; Domonkos Sik,; Renáta Németh,

doi:10.24365/ef.v62i4.6960

Eszter Katona Eötvös Loránd University, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Hungary
Domonkos Sik Eötvös Loránd University, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Hungary
Renáta Németh Eötvös Loránd University, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Hungary

DOI: https://doi.org/10.24365/ef.v62i4.6960

Keywords: depression, online forum, natural language processing, topic model, latent Dirichlet allocation, biopsychosocial model

Abstract

Online depression forums hold many potentials: beside providing information to those, who have otherwise difficulties of seeking advice; they also play a much needed intermediator role by translating expert knowledge to lay language, which is particularly important in the process of establishing acceptable ‘illness narratives’; finally, they provide peer support, which has the potential of establishing missing intersubjectivities. The aim of the research is to analyze the specific discursive functions of the biomedical, psychological and social narratives.

Author Biographies

Eszter Katona, Eötvös Loránd University, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Hungary

Domonkos Sik, Eötvös Loránd University, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Hungary

Renáta Németh, Eötvös Loránd University, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Hungary

References

Németh, R., Sik, D., & Katona, E. (2021). The asymmetries of the biopsychosocial model of depression in lay discourses — Topic modelling online depression forums. SSM — Population Health, 14, 100785. doi: 10.1016/j.ssmph.2021.100785

Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. The Journal of Machine Learning Research, 3, 993–1022.

Németh, R., Katona, E., & Kmetty, Z. (2020). Az automatizált szövegelemzés perspektívája a társadalomtudományokban. Szociológiai Szemle, 30(1), 44–62.

Article review: Automated text analysis of topics represented on depression forums using the biopsychosocial model of depression

Abstract

Author Biographies

References