Exploring the Use of Machine Learning to Automate the Qualitative Coding of Church-related Tweets
This article builds on previous research around the exploration of the content of church-related tweets. It does so by exploring whether the qualitative thematic coding of such tweets can, in part, be automated by the use of machine learning. It compares three supervised machine learning algorithms...
| Authors: | ; ; |
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| Format: | Electronic Article |
| Language: | English |
| Check availability: | HBZ Gateway |
| Journals Online & Print: | Drawer...
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| Fernleihe: | Fernleihe für die Fachinformationsdienste |
| Published: |
Equinox
[2019]
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| In: |
Fieldwork in religion
Year: 2019, Volume: 14, Issue: 2, Pages: 140-159 |
| Standardized Subjects / Keyword chains: | B
Church
/ Online community
/ Twitter (Softwareplattform)
/ New media
/ Artificial intelligence
/ Algorithms
/ Communication
/ Quality improvement
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| IxTheo Classification: | CB Christian life; spirituality CD Christianity and Culture CF Christianity and Science FD Contextual theology |
| Further subjects: | B
social media research
B digital theology B sociology of religion B Machine Learning |
| Online Access: |
Volltext (doi) |