• Journal of the Daesoon Academy of Sciences
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• v.27
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• pp.135-169
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• 2016

While examining the religious ideas implied by Jeungsan's Great Works of the Reordering of Universe, we find special ideas which cannot be found in any other religions, and these ideas are presented in diverse ways. Most of all, the representative idea is that of human nobility; a distinctive idea which makes Daesoonjinrihoe different from other religions. Thus, this research focuses on the following questions: when was Human Nobility concretely realized? What kind of organic relationship does human nobility have between the divine world and the world of humanity? In light of the forthcoming Era of Human Nobility, what are some concrete images which can be drawn from the interaction between the realms of heaven and humanity wherein preordinations are plotted in heaven and then carried out by humankind? Prior to formulating my own sense of the subject matter, I consulted 43 previous discussions and dissertations and arranged them chronologically so as to examine their correlation. From these sources and my own insights, I was able to gain a sense of the starting point of the era of human nobility and its tenor. I have found the following problems in previous research on the uniqueness and distinctness of human nobility: ①The conceptual undertones of human nobility have not been adequately gleaned. ②There do not seem to be any dissertations which examine the way in which human nobility is connected with the doctrines of the creative conjunction between yin and yang, the harmonious union of divine beings and human beings, and the resolution of grievances for mutual beneficence. ③In most dissertations, not only is the starting point of the Era of Human Nobility regarded as concurrent with the start of the 50,000 years of earthly paradise in the Later World, but also the point of division between the former world and the later world is widely disputed. ④In-depth and fully realized studies dealing with the subject of human nobility are not easily found. ⑤There is little sense of progression in the research on human nobility because scholars are not sufficiently engage with one another to achieve common consensus. Therefore, in this dissertation, I have provided answers to the problems I discovered in previous research. I have developed my own tenor as follows: ①By giving priority to the Jeongyeong, I have closely investigated the period which divides the Former World and the Later World. Then, I produced a chronological timeline to demonstrate the progression: the Former World → the Era of the Resolution of Grievances → the Later World. This aids in the comprehension of human nobility. ②The Era of Human Nobility was preceeded by the opening of the Era of the Resolution of Grievances of human world which began in 1901. Human nobility is stipulated as a regulatory system for the universe set in motion by the opening the Era of Resolution of Grievances. ③While synthetically examining the aspects of transition which enable the Ear of Human Nobility to be realized, the period to be studied is stipulated as beginning from 1901 and ending at the start of the Later World. The subjects are defined as the flowing from Jeungsan, the first leader of human nobility, to the noble individuals empowered by Dao and the noble populace. In the Era of Human Nobility, studying the transition process by which human nobility is realized requires delving into the resolution of grievances. Although this method is essential to understanding Daesoon ideas, in actuality it does not hinge upon speculative exegetical theorizing but instead it was gained through eisegetical rigor.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.107-129
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• 2022

It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.