This study aims at the description of ecological connection between body and earth(nature) through dances, rituals, and body movements. Referring to some dance studies which assume the body-earth connection as a lever for the realization of ecological relationality, this article illuminates some cases of ecologically related dances, rituals and body movements. In the first, this article reviews recent discourses of philosophy, anthropology, and dance studies on ecological consciousness, experience, ontology, and ecosomatic perception. Recent academic discourses emphasize that the connection is realized by the non-hierarchical relation, free from the perspective of dualism, between human being and ‘more-than-human’ world. Secondly, this article describes concrete cases. The cases show participants’ experiences of various ways or modes of connection, respectively; attentive efforts toward subtle energy in connection, immersion into the ecological world, surrender to earth, sensing reciprocity, realization of body as microcosm of earth, becoming other being and ontological transformation. In sum, this study describes people’s experience of the ecological world connected by dances, rituals and body movements.

The purpose of this study is to develop interdisciplinary research between dance studies and big data analysis. To this end, the text mining technique, which extracts meaningful information from text, was adopted as the research methodology. In the process of text mining, original PDF texts on the themes of Chum/Muyong(dance), morphological analysis, user dictionary construction, and social network analysis were collected to extract significant named entities and clarify the relations between them. The outcomes of the process, which comprised the extracted text data (total 10,231 copies), a named entity classification table, and a network of named entities, were loaded into the big data analysis system under development. The findings of the study are as follows: First, there were 25 total morpheme types, with 24,691 words with a frequency of more than 100. From these, a second morphemic analysis of sentences containing words such as “Chum” (춤), “Mu” (무), and “dance” (댄스) was conducted. It was revealed that in parts of speech with a frequency of 10 or more, there were 3,057 nouns, 602 proper nouns, 352 verbs, 205 numbers, 135 adjectives, and 35 adverbs. Second, a user dictionary was developed in the form of a taxonomy with stratification between hyperonym and hyponyms. The dictionary contained 2,404 words, which were classified by theme, person, dance piece, genre, theory, function, element, and period. Third, social network analysis revealed that the terms “Muyong,” “Chum,” and “arts and culture” were closely interconnected at the heart of the network. In contrast, dance deviated somewhat from the center. “Dance” was the only word to be connected with the network of dance sports and jazz. This study is significant because it represents the first attempt to apply text mining to written records on dance. In addition, it could suggest ways to expand the use of big data analysis to dance studies. Based on the study, a big data analysis system that is specialized in dance was developed, and the contents will be updated continuously.