Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.

In this paper, we seek to identify the existing conceptualisations and applications of social capital contained in the literature, as well as how these are used and combined across and within research fields. Our analytical approach presents a unique combination of topic models and bipartite blockmo...

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Autores principales:	Jef Vlegels, Stijn Daenekindt
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e939a0295ff64fe0b275bf4089b58726
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spelling	oai:doaj.org-article:e939a0295ff64fe0b275bf4089b587262021-12-02T20:10:21ZCombining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.1932-620310.1371/journal.pone.0253478https://doaj.org/article/e939a0295ff64fe0b275bf4089b587262021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0253478https://doaj.org/toc/1932-6203In this paper, we seek to identify the existing conceptualisations and applications of social capital contained in the literature, as well as how these are used and combined across and within research fields. Our analytical approach presents a unique combination of topic models and bipartite blockmodelling, enabling us to analyse both the content and structures of a large collection of academic texts. In particular, this allows us to: (a) summarise the content in relation to a variety of topics; and (b) uncover the structure, with diverse text subsets engaging differently with these topics. Our analysis of all of the 11,975 articles on Web of Science that address 'social capital' demonstrates that these can be reduced to nine distinct topic clusters and six article clusters. Specifically, we identify the multifaceted nature of the social-capital metaphor and show that there are clear variations in how it is deployed in different bodies of literature. Finally, by mapping the diverse conceptualisations and applications of social capital in a network, we propose a tool for identifying future research opportunities for those interested in novel social-capital treatments in their field.Jef VlegelsStijn DaenekindtPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 6, p e0253478 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jef Vlegels Stijn Daenekindt Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.
description	In this paper, we seek to identify the existing conceptualisations and applications of social capital contained in the literature, as well as how these are used and combined across and within research fields. Our analytical approach presents a unique combination of topic models and bipartite blockmodelling, enabling us to analyse both the content and structures of a large collection of academic texts. In particular, this allows us to: (a) summarise the content in relation to a variety of topics; and (b) uncover the structure, with diverse text subsets engaging differently with these topics. Our analysis of all of the 11,975 articles on Web of Science that address 'social capital' demonstrates that these can be reduced to nine distinct topic clusters and six article clusters. Specifically, we identify the multifaceted nature of the social-capital metaphor and show that there are clear variations in how it is deployed in different bodies of literature. Finally, by mapping the diverse conceptualisations and applications of social capital in a network, we propose a tool for identifying future research opportunities for those interested in novel social-capital treatments in their field.
format	article
author	Jef Vlegels Stijn Daenekindt
author_facet	Jef Vlegels Stijn Daenekindt
author_sort	Jef Vlegels
title	Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.
title_short	Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.
title_full	Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.
title_fullStr	Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.
title_full_unstemmed	Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.
title_sort	combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/e939a0295ff64fe0b275bf4089b58726
work_keys_str_mv	AT jefvlegels combiningtopicmodelswithbipartiteblockmodellingtouncoverthemultifacetednatureofsocialcapital AT stijndaenekindt combiningtopicmodelswithbipartiteblockmodellingtouncoverthemultifacetednatureofsocialcapital
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Combining topic models with bipartite blockmodelling to uncover the multifaceted nature of social capital.

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