• Asian Journal for Public Opinion Research
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• v.3 no.2
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• pp.106-109
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• 2016

• Asian Journal for Public Opinion Research
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• v.1 no.1
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• pp.65-70
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• 2013

• Asian Journal for Public Opinion Research
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• v.7 no.3
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• pp.199-204
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• 2019

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.141-157
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• 2021

In this study, we aimed to understand research trends of domestic artificial intelligence research. To achieve the goal, we applied network analysis and dynamic topic modeling to domestic research papers on artificial intelligence. Among the papers that have been indexed in KCI (Korean Journal of Citation Index) by 2020, metadata and abstracts of 2,552 papers where the titles or indexed keywords include 'artificial intelligence' both in Korean and English were collected. Keyword, affiliation, subject field, and abstract were extracted and preprocessed for further analyses. We identified main keywords in the field by analyzing keyword co-occurrence networks as well as the degree and characteristics of research collaboration between domestic and foreign institutions and between industry and university by analyzing institutional collaboration networks. Dynamic topic modeling was performed on 1845 abstracts written in Korean, and 13 topics were obtained from the labeling process. This study broadens the understanding of domestic artificial intelligence research by identifying research trends through dynamic topic modeling from abstracts as well as the degree and characteristics of research collaboration through institutional collaboration networks from author affiliation information. In addition, the results of this study can be used by governmental institutions for making policies in accordance with artificial intelligence era.

• Journal of Contemporary Eastern Asia
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• v.15 no.1
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• pp.1-3
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• 2016

• Journal of Contemporary Eastern Asia
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• v.17 no.2
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• pp.234-236
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• 2018

• The Research Journal of the Costume Culture
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• v.28 no.2
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• pp.265-284
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• 2020

This study aimed to analyze the performance of Disney-collaborated fashion lines based on online consumer reviews. To do so, the researchers employed text mining and network analysis to identify key words in the reviews of these products. Blogs, internet cafes, and web documents provided by Naver, Daum, and YoutTube were selected as subjects for the analysis. The analysis period was limited to one year after for the 2019. Data collection and analysis were conducted using Python 3.7, Textom, and NodeXL. The research terms in question were as follows: 'Disney fashion collaboration' and 'Frozen fashion collaboration'. Preliminary survey results indicated that 'Elsa's dress' was the most frequently mentioned term and that the domestic fashion brand Eland Retail was the most active in selling Disney branded clothing through its own brand. The writers of reviews for Disney-collaborated fashion products were primarily mothers with daughters. Their decision to purchase these products was based upon the following factors; price, size, stability of decoration, shipping, laundry, and retailer. The motives for purchasing the product were the positive response of the consumer's child and the satisfaction of the parents due to the child's response. The problems to be solved included insufficient quantity of supply, delay in delivery, expensive price considering the number of times children's clothes are worn, poor glitter decoration, faded color, contamination from laundry, and undesirable smells immediately after the purchase.

• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.53-84
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• 2016

This study clarified the intellectual structure of international collaboration in psychiatry based on analyzing networks in order to vitalize for international collaboration in psychiatry in South Korea. The data set was collected from Web of Science citation database during the period from 2009 to 2013. SU="psychiatry" search formulary (means field of psychiatric medical research) was used through advanced retrieval function and a total of 18,590 articles were selected among international collaborations. A total of 85 different keywords were selected from the 18,590 articles, and the results of analysis were as follows. First, this study examined 8 sub-subject areas focusing on disorders, and found that major subject areas could be divided into a total of 8 sub-subject areas. Second, this study examined 6 keywords that have a strong impact, and extend subject areas by promoting intermediation between other keywords Third, this study examined sub-subject areas by using the Knowledge Classification Scheme of the National Research Foundation of Korea through community analysis, and found a total of 15 clusters and a total of 12 sub-subject areas.

• Journal of Information Management
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• v.36 no.1
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• pp.77-101
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• 2005

The purpose of this paper is to examine some aspects of international collaboration in the age of digital technologies. First, the paper describes the longitudinal structure of collaborative pattern among the 10 East-Asian countries based on their frequency of co-authoring SCI journal articles in the year 2001-2003. Second, a focus interview was made to explore the way in which new digital technologies such as the Internet have changed a research practice in the field of science, technology, and innovation. This research found that Japan and China are preferred as the number one collaborator by other Asian countries. Their share of international collaboration with other Asian countries has been increasing in three years. The results of indepth interview with a scholar suggest that digital network technologies have several advantages enabling individual and institutional actors to collaborate with each other effectively in terms of knowledge management as well as information exchange.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.9-16
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• 2014

In recent years, the importance of IoT (Internet of Things) is emphasized by information communication technologies and the performance of various smart devices are rapidly developed and applied in the real world. In this paper, we propose a process-driven IoT-object collaboration model to specify and execute a IoT service based on processes. That is, the purpose of this paper is to suggest a formal method in order to describe a IoT service into a group of tasks having execution order and collaboration between IoT-objects in charge of the enactment of a task. Conclusively, through the proposed model, we expect that IoT services will be automatically executed, analyzed, monitored and reused in the process-driven IoT computing environment.