• Fashion & Textile Research Journal
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• v.21 no.3
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• pp.277-287
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• 2019

This study analyzes the online issues of design innovation by a fashion creative director. The study selected fashion house Gucci as the main subject and analyzed social media posts. As for study methods, a social matrix program Textom 2.0 collected 13,014 nouns and adjectives using 'Gucci Collection' as a search keyword from Naver Blogs from March to August 2014 and from March to August 2016. Design related issues were derived through semantic network analysis using Ucinet6 and the NetDraw program. The results of the keyword frequency analysis showed that social media user interest for the Gucci collection increased based on the rapid increase in the number of posts from 1,064 to 2,126 after changing the fashion creative director. The results of visualization of semantic network analysis and content analysis also showed that the main issues related to the Gucci collection design changed after the replacement of the fashion creative director. The study found that issues formed around the product information worn by celebrities for promotion purposes during the 2014 period; however, during the 2016 period, issues were formed around 'vintage' and 'retro' runway concepts with design styles related to Alessandro Michele, the new creative director.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.95-115
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• 2022

The purpose of this study is to transform the sub-categorization terms of the National Science and Technology Standards Classification System into technical keywords by applying a machine learning algorithm. For this purpose, AttentionMeSH was used as a learning algorithm suitable for topic word recommendation. For source data, four-year research status files from 2017 to 2020, refined by the Korea Institute of Science and Technology Planning and Evaluation, were used. For learning, four attributes that well express the research content were used: task name, research goal, research abstract, and expected effect. As a result, it was confirmed that the result of MiF 0.6377 was derived when the threshold was 0.5. In order to utilize machine learning in actual work in the future and to secure technical keywords, it is expected that it will be necessary to establish a term management system and secure data of various attributes.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.327-339
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• 2010

The cultural contents are a field that originally has a cycle ranged from producers of various contents and distribution consumption. The various object elements composing of an ecosystem of cultural contents in this cycle, and the search of harmonious relations between these objects is becoming an important issue. The ecological approach on the cultural contents field is not being tried authentically until now, in spite of the expansion of interest and usefulness from its application at present, so there is no detailed discussion on the inside of an ecosystem and its action such as confirmation of object elements composing of the ecosystem, interaction principles between objects and object development, principles of co-evolution, etc. achieving common development of all objects composing of the ecosystem. Therefore, the present research aims to confirm object elements composing of the ecosystem of cultural contents through an ecosystem model that has been researched in several fields of the ecosystem and social science, and to seek interaction between objects and each object as well as a development direction of a total ecosystem.

• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.265-270
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• 2022

With the implementation of the fox restoration project, the number of foxes released into nature are increasing; therefore, in the future, foxes will be dispersed to other areas and will appear in human habitats. In this study, the habitat suitability index (HSI) of foxes was developed to predict and prepare for the effects. After extracting major environmental variables through literature research and GIS analysis, 5 suitability indices (SIs) were constructed. The forest physiognomy, slope, aspect, distance from water source, and distance from road are the main variables, and the arithmetic average value by giving twice the weight to the forest physiognomy is the HSI result. As a result of comparing with the data from the Natural Environment Survey, it is found that the fox coordinates have an average HSI value of 0.64, and the probability of appearance is high when it is 0.53 or higher. Using the results of this study, it is expected to be able to predict the distribution of foxes in advance, to use them as basic data for future restoration plans, or to identify the distribution of the species and the reduction plan in future environmental impact assessments.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.91-102
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• 2014

The purpose of this research is to perform the consumer typological study of integrated emerging digital advertisement, where IT and advertisement industry were fused, and to propose the theoretical definition about consumer characteristic which is in need for collection of related market subdivision strategy in perspective of business marketing. For this, the Q methodology, the 'subjectivity' research of qualitative perspective, which discovers new theory by interpreting subjective system of thinking, preference, opinion, and recognition of inner side of respondents, was applied and analyzed. Compared to previous quantitative research that pursues hypothesis verification, this Q methodology is not dependent on operational definition proposed by researcher but pursues for analytic study completely reflecting objective testimony of respondents. For this reason, Q study analyzes in-depth the actual consumer type, which can be found at the initial market formation stage of new service, therefore this study is applicable for theorizing the consumer character as a mean of advanced research. This study extracted thirty 'IT integrated digital advertisement type (Q sample)' from thorough literature research and interviews, and eventually discovered a total four consumer types from analyzing each Q sorting research data of 40 respondents (P sample). Moreover, by interpreting subdivided intrinsic characteristic of each group, the four types were named as 'multi-channel digital advertisement pursuit type', 'emotional advertisement pursuit type', 'new media advertisement pursuit type', and Web 2.0 advertisement pursuit type'. The analysis result of this study is being expected for its value of usage as advanced research of academic and industrial research with the emerging digital advertisement industry as a subject, and as basic research in the field of R&D, Marketing program and the field of designing the advertisement creative strategy and related policy.