Understanding China through Big Data: applications of theory-oriented quantitative approaches
Chen, He and Yan present a range of applications of multiple-source big data to core areas of contemporary sociology, demonstrating how a theory-guided approach to macrosociology can help to understand social change in China, especially where traditional approaches are limited by constrained and bia...
Gespeichert in:
Hauptverfasser: | , , |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
London ; New York
Routledge, Taylor & Francis Group
2022
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Schriftenreihe: | Routledge advances in sociology
314 |
Schlagworte: | |
Zusammenfassung: | Chen, He and Yan present a range of applications of multiple-source big data to core areas of contemporary sociology, demonstrating how a theory-guided approach to macrosociology can help to understand social change in China, especially where traditional approaches are limited by constrained and biased data.In each chapter of the book, the authors highlight an application of theory-guided macrosociology that has the potential to reinvigorate an ambitious, open-minded and bold approach to sociological research. These include social stratification, social networks, medical care, and online behaviours among many others. This research approach focuses on macro-level social process and phenomena by using quantitative models to statistically test for associations and causalities suggested by a clearly hypothesised social theory. By deploying theory-oriented macrosociology where it can best assure macro-level robustness and reliability, big data applications can be more relevant to and guided by social theory. An essential read for sociologists with an interest in quantitative and macro-scale research methods, which also provides fascinating insights into Chinese society as a demonstration of the utility of its methodology |
Beschreibung: | xiii, 257 Seiten Illustrationen, Diagramme |
ISBN: | 9780367758264 9780367758257 |
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Datensatz im Suchindex
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author | Chen, Yunsong He, Guangye Yan, Fei |
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geographic | China (DE-588)4009937-4 gnd |
geographic_facet | China |
id | DE-604.BV049010021 |
illustrated | Illustrated |
index_date | 2024-07-03T22:11:20Z |
indexdate | 2024-07-20T03:24:09Z |
institution | BVB |
isbn | 9780367758264 9780367758257 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034273098 |
oclc_num | 1392143004 |
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physical | xiii, 257 Seiten Illustrationen, Diagramme |
publishDate | 2022 |
publishDateSearch | 2022 |
publishDateSort | 2022 |
publisher | Routledge, Taylor & Francis Group |
record_format | marc |
series | Routledge advances in sociology |
series2 | Routledge advances in sociology |
spelling | Chen, Yunsong Verfasser (DE-588)120015391X aut Understanding China through Big Data applications of theory-oriented quantitative approaches Yunsong Chen, Guangye He, and Fei Yan London ; New York Routledge, Taylor & Francis Group 2022 xiii, 257 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Routledge advances in sociology 314 Chen, He and Yan present a range of applications of multiple-source big data to core areas of contemporary sociology, demonstrating how a theory-guided approach to macrosociology can help to understand social change in China, especially where traditional approaches are limited by constrained and biased data.In each chapter of the book, the authors highlight an application of theory-guided macrosociology that has the potential to reinvigorate an ambitious, open-minded and bold approach to sociological research. These include social stratification, social networks, medical care, and online behaviours among many others. This research approach focuses on macro-level social process and phenomena by using quantitative models to statistically test for associations and causalities suggested by a clearly hypothesised social theory. By deploying theory-oriented macrosociology where it can best assure macro-level robustness and reliability, big data applications can be more relevant to and guided by social theory. An essential read for sociologists with an interest in quantitative and macro-scale research methods, which also provides fascinating insights into Chinese society as a demonstration of the utility of its methodology Big Data (DE-588)4802620-7 gnd rswk-swf Makrosoziologie (DE-588)4168687-1 gnd rswk-swf Sozialer Wandel (DE-588)4077587-2 gnd rswk-swf China (DE-588)4009937-4 gnd rswk-swf China (DE-588)4009937-4 g Big Data (DE-588)4802620-7 s Sozialer Wandel (DE-588)4077587-2 s Makrosoziologie (DE-588)4168687-1 s DE-604 He, Guangye Verfasser (DE-588)120576528X aut Yan, Fei Verfasser (DE-588)1172381593 aut Erscheint auch als Online-Ausgabe 978-1-003-16416-6 Routledge advances in sociology 314 (DE-604)BV013741699 314 |
spellingShingle | Chen, Yunsong He, Guangye Yan, Fei Understanding China through Big Data applications of theory-oriented quantitative approaches Routledge advances in sociology Big Data (DE-588)4802620-7 gnd Makrosoziologie (DE-588)4168687-1 gnd Sozialer Wandel (DE-588)4077587-2 gnd |
subject_GND | (DE-588)4802620-7 (DE-588)4168687-1 (DE-588)4077587-2 (DE-588)4009937-4 |
title | Understanding China through Big Data applications of theory-oriented quantitative approaches |
title_auth | Understanding China through Big Data applications of theory-oriented quantitative approaches |
title_exact_search | Understanding China through Big Data applications of theory-oriented quantitative approaches |
title_exact_search_txtP | Understanding China through Big Data applications of theory-oriented quantitative approaches |
title_full | Understanding China through Big Data applications of theory-oriented quantitative approaches Yunsong Chen, Guangye He, and Fei Yan |
title_fullStr | Understanding China through Big Data applications of theory-oriented quantitative approaches Yunsong Chen, Guangye He, and Fei Yan |
title_full_unstemmed | Understanding China through Big Data applications of theory-oriented quantitative approaches Yunsong Chen, Guangye He, and Fei Yan |
title_short | Understanding China through Big Data |
title_sort | understanding china through big data applications of theory oriented quantitative approaches |
title_sub | applications of theory-oriented quantitative approaches |
topic | Big Data (DE-588)4802620-7 gnd Makrosoziologie (DE-588)4168687-1 gnd Sozialer Wandel (DE-588)4077587-2 gnd |
topic_facet | Big Data Makrosoziologie Sozialer Wandel China |
volume_link | (DE-604)BV013741699 |
work_keys_str_mv | AT chenyunsong understandingchinathroughbigdataapplicationsoftheoryorientedquantitativeapproaches AT heguangye understandingchinathroughbigdataapplicationsoftheoryorientedquantitativeapproaches AT yanfei understandingchinathroughbigdataapplicationsoftheoryorientedquantitativeapproaches |