Mapping Knowledge Structure in Mystical Researches: A Co-Word Analysis

By using co-word analysis, knowledge structure can be determined in a research field and its topical clusters can be identified. This research tries to study knowledge structure in mystical researches via this method and by using network analysis approaches and science visualization. The population of the current study is comprised of 1931 published articles in the field of mysticism that have been indexed in Islamic World Science Citation Center (ISC). By using scientometric and network analysis techniques, the records were retrieved and integrated. It has been used a combination of softwares, including UCINet, VosViewer and SPSS, for data analysis and mapping. Analyzing all keywords show that the most important keywords, based on frequency distribution, are top figures of mysticism: Rumi (Mulavi) and Ibn-Arabi, also Love. As in the co-word analysis, keywords’ pairs such as “Rumi-Masnavi”, “manifestation-unity of existence”, “Ibn-Arabi-unity of existence” have the most frequent co-occurrences. Analyzing lexical clusters show the most important topics related to mystical research in eleven clusters with diverse titles. Based on multidimensional scaling map, these eleven clusters are decreased into eight ones with more general topics, more conjunction and similarity. Studying the centrality and density of these clusters- which indicate maturity and development of each topic based on its keywords- in strategic diagram show that Hekmat (theosophy) or theoretical mysticism, especially from Ibn-Arabi’s point of view, not only have development ability, but also most central role among other topics.