Preaching to Social Media: Turkey’s Friday Khutbas and Their Effects on Twitter

Ozan Aksoy
Additional contact information
Ozan Aksoy: Centre for Quantitative Social Sciences in the Social Research Institute, University College London

No 21-17, DoQSS Working Papers from Quantitative Social Science - UCL Social Research Institute, University College London

Abstract: In this study I analyse through machine learning the content of all Friday khutbas (sermons) read to millions of citizens in thousands of Mosques of Turkey since 2015. I focus on six non-religious and recurrent topics that feature in the sermons, namely business, family, nationalism, health, trust, and patience. I demonstrate that the content of the sermons responds strongly to events of national importance. I then link the Friday sermons with ~4.8 million tweets on these topics to study whether and how the content of sermons affects social media behaviour. I find generally large effects of the sermons on tweets, but there is also heterogeneity by topic. It is strongest for nationalism, patience, and health and weakest for business. Overall, these results show that religious institutions in Turkey are influential in shaping the public’s social media content and that this influence is mainly prevalent on salient issues. More generally, these results show that mass offline religious activity can have strong effects on social media behaviour

Keywords: text-as-data analysis; computational social science; social media; religion; Islam; Turkey (search for similar items in EconPapers)
JEL-codes: C63 N35 Z12 (search for similar items in EconPapers)
Date: 2021-05-01
New Economics Papers: this item is included in nep-ara, nep-big, nep-cmp and nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://repec.ioe.ac.uk/REPEc/pdf/qsswp2117.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:qss:dqsswp:2117

Access Statistics for this paper

More papers in DoQSS Working Papers from Quantitative Social Science - UCL Social Research Institute, University College London Quantitative Social Science, Social Research Institute, 55-59 Gordon Square, London WC1H 0NU. Contact information at EDIRC.
Bibliographic data for series maintained by Dr Neus Bover Fonts ().