2016
DOI: 10.1007/978-3-319-39445-9_6
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Phylogenetics Meets Folklore: Bioinformatics Approaches to the Study of International Folktales

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Cited by 11 publications
(11 citation statements)
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“…Through the statistical analysis, the study highlights the efficiency of Bayesian statistics in quantitatively analyzing a cultural phenomenon ("cultural additivity") using traditionally qualitative materials, i.e., Vietnamese folkloric literature. This method adds to the exploration of using texts as social and cultural data explored in previous work of computational folkloristics and sociolinguistics (Nguyen, 2017;Bortolini et al, 2017a;Tehrani and d'Huy, 2017;Abello et al, 2012;Tangherlini, 2013; Da Silva and Tehrani, 2016; Youngblood and Lahti, 2018). However, similar to the shortcomings of other computational works of folktales (Tehrani and d'Huy, 2017), the coding of the dataset in this study is determined by an individual researcher.…”
Section: Discussionmentioning
confidence: 99%
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“…Through the statistical analysis, the study highlights the efficiency of Bayesian statistics in quantitatively analyzing a cultural phenomenon ("cultural additivity") using traditionally qualitative materials, i.e., Vietnamese folkloric literature. This method adds to the exploration of using texts as social and cultural data explored in previous work of computational folkloristics and sociolinguistics (Nguyen, 2017;Bortolini et al, 2017a;Tehrani and d'Huy, 2017;Abello et al, 2012;Tangherlini, 2013; Da Silva and Tehrani, 2016; Youngblood and Lahti, 2018). However, similar to the shortcomings of other computational works of folktales (Tehrani and d'Huy, 2017), the coding of the dataset in this study is determined by an individual researcher.…”
Section: Discussionmentioning
confidence: 99%
“…This method adds to the exploration of using texts as social and cultural data explored in previous work of computational folkloristics and sociolinguistics (Nguyen, 2017;Bortolini et al, 2017a;Tehrani and d'Huy, 2017;Abello et al, 2012;Tangherlini, 2013; Da Silva and Tehrani, 2016; Youngblood and Lahti, 2018). However, similar to the shortcomings of other computational works of folktales (Tehrani and d'Huy, 2017), the coding of the dataset in this study is determined by an individual researcher. Therefore, the dataset and results will always be at risk of being influenced by personal biases.…”
Section: Discussionmentioning
confidence: 99%
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“…Although fairy tales have existed for several thousand years (da Silva & Tehrani, 2016;Tehrani & d'Huy, 2017), they have increasingly been used to invite consumers to imagine themselves as part of heroic magical quests towards magical transformation (Belk, Ger & Askegaard, 2003;Rotmann, 2017).…”
Section: Discussionmentioning
confidence: 99%
“…Indeed, while scholars have pointed out the prevalence of elements related to violence and lies in folktales (Meehan, 1994;Victor, 1990;Haar, 2005;Chima and Helen, 2015;Alcantud-Diaz, 2010, few have offered a rigorous statistical method to understand the interactions between these elements and their religio-cultural contexts. Thus, the present study's research method adds to the wave of studies on computational folkloristics, which currently emphasize the digitization of resources, the classification of folklore, and the necessary algorithms for data structure development rather than the statistical analysis of behavioral patterns in folktales (Abello et al, 2012;Tangherlini, 2013;Nguyen et al, 2013;Dogra, 2018;Tehrani and d'Huy, 2017). Moreover, the scope of the present research differs from the largely Euro-centric research projects (Nguyen et al, 2013;Bortolini et al, 2017a, b;d'Huy et al, 2017;Nikolić and Bakarić, 2016), as it contributes to the wave of scholarship on non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies by shedding light on the littleknown behavioral variability and contradictions in the folklore of a developing Asian country (Henrich et al, 2010).…”
Section: Introductionmentioning
confidence: 99%