TY - JOUR
T1 - The sacred and the profane
T2 - social media and temporal patterns of religiosity in the United Arab Emirates
AU - Thomas, Justin
AU - Al Shehhi, Aamna
AU - Grey, Ian
N1 - Publisher Copyright:
© 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2019/9/2
Y1 - 2019/9/2
N2 - Large datasets associated with internet search engines and social media platforms are increasingly used to study psychological variables. Over the past decade, ‘big data’, as they have become known, have become central to the exploration of a diverse range of topics. Few studies, however, have examined religiosity (religious belief, commitment, and devotion), particularly Islamic religiosity in the Arab world. This study looked at religiosity in the United Arab Emirates through data extracted from Twitter, a popular social media platform. The data comprised 152 million Twitter messages, spanning the period 1 April–30 September 2016. Bilingual search algorithms were employed to investigate the temporal patterns of religiosity expressed within the dataset. The study also explored patterns in the expression of obscenity (offensive language), hypothesising a negative relationship with religious sentiment. Religiosity followed hypothesised temporal patterns and was also inversely correlated with obscenity. There were differences observed between languages (Arabic vs English) and gender, with males, surprisingly, expressing greater religiosity than females. This research contributes to the nascent study of religiosity through social media.
AB - Large datasets associated with internet search engines and social media platforms are increasingly used to study psychological variables. Over the past decade, ‘big data’, as they have become known, have become central to the exploration of a diverse range of topics. Few studies, however, have examined religiosity (religious belief, commitment, and devotion), particularly Islamic religiosity in the Arab world. This study looked at religiosity in the United Arab Emirates through data extracted from Twitter, a popular social media platform. The data comprised 152 million Twitter messages, spanning the period 1 April–30 September 2016. Bilingual search algorithms were employed to investigate the temporal patterns of religiosity expressed within the dataset. The study also explored patterns in the expression of obscenity (offensive language), hypothesising a negative relationship with religious sentiment. Religiosity followed hypothesised temporal patterns and was also inversely correlated with obscenity. There were differences observed between languages (Arabic vs English) and gender, with males, surprisingly, expressing greater religiosity than females. This research contributes to the nascent study of religiosity through social media.
KW - Islam
KW - profanity
KW - Religion
KW - social media
KW - Twitter
UR - http://www.scopus.com/inward/record.url?scp=85073185190&partnerID=8YFLogxK
U2 - 10.1080/13537903.2019.1658937
DO - 10.1080/13537903.2019.1658937
M3 - Article
AN - SCOPUS:85073185190
SN - 1353-7903
VL - 34
SP - 489
EP - 508
JO - Journal of Contemporary Religion
JF - Journal of Contemporary Religion
IS - 3
ER -