Izvorni znanstveni članak
https://doi.org/10.21860/j.13.2.9
A Study on the Analysis of the Interrelationship between the Epic of Gilgamesh and the Bible Using Text Mining: Focusing on the Episode of the Great Flood
Jihoon Kang
; Institute for Mediterranean Studies, Busan University of Foreign Studies, Busan, Republic of Korea
Sujung Kim
; Department of Arab Studies, Busan University of Foreign Studies, Busan, Republic of Korea
Sažetak
The development of human civilization is a continuous process of imitation and creation based on exchange. Most historical research is performed qualitatively, so consequently, historical interpretations tend to be biased with personal or subjective viewpoints. In this context, Bible is the most-read book in history and comparative studies are steadily conducted owing to its similarities with the myths of ancient civilizations. This study combines qualitative and quantitative analysis to analyze the interrelationship between a myth and the Bible. Specifically, intertextuality analysis was performed around the great flood episode in Mesopotamia’s Epic of Gilgamesh and the Bible’s Genesis. Text mining–based association rule analysis and word cloud analysis were combined to verify this. Intertextuality analysis revealed the interrelationship between the Epic of Gilgamesh and the Bible; moreover, text mining helped verify the association in intertextuality analysis. Through this, the study proposes a research method for civilization exchange studies by objectively approaching the flow and directionality of exchanges among civilizations in the ancient Mediterranean regions. Furthermore, along with civilization exchange studies, a practical convergent research method for studies in the areas of humanities, regional studies, and history was suggested.
Ključne riječi
Data science; Epic of Gilgamesh; Great flood; Mesopotamia; Myth; Mesopotamian civilization; Bible; Text mining; Association analysis; Civilization Exchange studies; Research methodology
Hrčak ID:
293300
URI
Datum izdavanja:
4.2.2023.
Posjeta: 1.372 *