• The Journal of the Korea Contents Association
• /
• v.20 no.6
• /
• pp.460-469
• /
• 2020

This study analyzes online news articles and cafe articles on the '5-day Rotation Mask Distribution System', which is emerging as a recent issue due to the COVID-19 incident, to identify the mass media and social media agendas containing media and public reactions. This study figured out the difference between mass media and social media. For analysis, we collected 2,096 full text articles from Naver and 1,840 posts from Naver Cafe, and conducted word frequency analysis, word cloud, and LDA topic modeling analysis through data preprocessing and refinement. As a result of analysis, social media showed real-life topics such as 'family members' purchase', 'the postponement of school opening', ' mask usage', and 'mask purchase', reflecting the characteristics of personal media. Social media was found to play a role of exchanging personal opinions, emotions, and information rather than delivering information. With the application of the research method applied to this study, social issues can be publicized through various media analysis and used as a reference in the process of establishing a policy agenda that evolves into a government agenda.

• Knowledge Management Research
• /
• v.21 no.3
• /
• pp.215-228
• /
• 2020

This study introduces the case of a company that newly jumped into the competitive cosmetics market with a brand concept developed through big data analysis. Skin Reverse Lab, which possesses anti-aging material technology, launched a new brand in the skincare cosmetics market. Using a big data analysis program called Luminoso, SNS data was analyzed in four areas, which were consumer attitudes toward overall cosmetics, skincare products, competitors, and consumers' experiences of product use. The age groups and competitors were analyzed through the emotional analysis technique including context, which is the strength of Luminoso, and insights on consumers were derived through the related word analysis and word cloud techniques. Based on the analysis results, Logically Skin have won various awards in famous magazines and apps, and have been recognized as products that meet global trend standards. Besides, it has entered six countries including the United States and Hong Kong. The Logically Skin case is a case in which a new company entered the market with a new brand by deriving consumer insights only from external data, and it is significant as a case of applying AI-based sentiment analysis.

• Fashion & Textile Research Journal
• /
• v.24 no.5
• /
• pp.593-604
• /
• 2022

The purpose of this study is to analyze the flow of change in perception of metaverse before and after COVID-19 through big data analysis. This research method used Textom to collect all data, including metaverse for two years before COVID-19 (2018.1.1~2019.11.30) and after COVID-19 outbreak (2020.1.11~2021.12.31), and the collection channels were selected by Naver and Google. The collected data were text mining, and word frequency, TF-IDF, word cloud, network analysis, and emotional analysis were conducted. As a result of the analysis, first, hotels, weddings, and glades were commonly extracted as social issues related to metaverse before and after COVID-19, and keywords such as robots and launches were derived, so the frequency of keywords related to hotels and weddings was high. Second, the association of the pre-COVID-19 metaverse keywords was platform-oriented, content-oriented, economic-oriented, and online promotion-oriented, and post-COVID-19 clusters were event-oriented, ontact sales-oriented, stock-oriented, and new businesses. Third, positive keywords such as likes, interest, and joy before COVID-19 were high, and positive keywords such as likes, joy, and interest after COVID-19. In conclusion, through this study, it was found that metaverse has firmly established itself as a new platform business model that can be used in various fields such as tourism, travel, festivals, and education using smart technology and metaverse.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.12
• /
• pp.111-119
• /
• 2022

The purpose of this paper is to examine the change in perception of 3D virtual fashion before and after COVID-19 using big data analysis. The data collection period is from January 1, 2017, before the outbreak of COVID-19, to October 30, 2022, after the outbreak. Big data was collected for key words related to 3D virtual fashion extracted from social media such as Naver, Daum, Google, and YouTube using Textom. After the collected words were refined, word cloud, word frequency, connection centrality, network visualization, and CONCOR analysis were performed. As a result of extracting and analyzing 32,461 words with 3D virtual fashion as a keyword, the frequency and centrality of fashion, virtual, and technology appeared the highest, and the frequency of appearance of digital, design, clothing, utilization, and manufacturing was also high. Through this, it was found that 3D virtual fashion is being used throughout the industry along with the development of technology. In particular, the key words that stand out the most after COVID-19 are metaverse and 3D education, which are in high demand in the fashion industry.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.3
• /
• pp.527-535
• /
• 2023

To develop experts capable of responding to cyber security incidents, numerous institutions have established cyber training facilities to cultivate security professionals equipped with effective defense strategies. However, these challenges such as limited resources, scenario-based content development, and cost constraints. To address these issues, this paper proposes a virtual infrastructure variation generation framework. It provides customized, diverse IT infrastructure environments for each organization, allowing cyber defense trainers to accumulate a wide range of experiences. By leveraging Infrastructure-as-Code (IaC) containers and employing Word2Vec, a natural language processing model, mutable code elements are extracted and trained, enabling the generation of new code and presenting novel container environments.

• Journal of Fashion Business
• /
• v.28 no.4
• /
• pp.1-20
• /
• 2024

The aim of this study was to analyze contemporary sociocultural phenomena and values through characteristics of augmented reality (AR) digital fashion design. The research method included a literature review on the metaverse and augmented reality, combined with a case study using both quantitative analysis through big data text mining and qualitative analysis through constant comparison. Data analysis was conducted using Python-based open-source tools: First, 6,725 data entries were collected from AR digital fashion platforms and brands identified in articles from Vogue and Vogue Business containing keywords of 'augmented reality' and 'digital fashion. Second, text preprocessing involved stop word removal, tokenization, and POS-tagging of nouns and adjectives using the NLTK library. Third, top 50 keywords were extracted through term frequency (TF) and TF-IDF analysis, with results visualized using a word cloud. Fourth, characteristics of products' external design and internal concepts that contained top keywords were classified, with their value examined through repeated comparison. Results indicate that AR digital fashion design has the following characteristics. First, it embodies surreal fantasy through designs that mimic natural biological patterns using 3D scanning and modeling technology. Second, it presents a trans-boundary aspect by utilizing the fluidity of body and space to challenge vertical and discriminatory social structures. Third, it imagines a new future transcending traditional sociocultural concepts by expanding perceptions of space and time based on advanced technological aesthetics. Fourth, it contributes to sustainability by exploring alternatives for the fashion industry in response to climate change and ecological concerns.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.1
• /
• pp.432-438
• /
• 2021

This dissertation's object is to confirm the drastic popularity of La Peste of Albert Camus in Korea post-corona society using big data as the mean of inductive research. Analyzing news articles concerning Camus and investigating word frequency of the book La Peste will affirm the implications La Peste has on current Korea society as the outbreak spreads. As an analysis tool, Bigkinds of Korea Press Foundation and Nuagedemots, the French version of Word Cloud were used. For the past 30 years, Albert Camus has been known in Korea as the writer of L'étranger, but after the epidemic, he earned more reputation with La Peste. Compared to L'étranger that rebelled against the world's absurdity with ennui, La peste emphasizes the importance of resistance accompanied by solidarity. La peste conveys hope by depicting disastrous situations of citizens who confront the plague by organizing a health college. The novel delivers a lot of ethical inspiration to humanity in this exceptional circumstance of COVID-19.

• Journal of Korean Society of Forest Science
• /
• v.110 no.1
• /
• pp.82-90
• /
• 2021

In this study, the validity of the forest therapy process, in which forest activities using forest therapy factors lead to immunity promotion and health promotion, was analyzed theoretically and qualitatively to refine and systemize the forest therapy concept. Research and analysis data were collected from the websites of institutions related to forest therapy; 33 theses and 33 original research articles from 2000 to March 2020 were searched for forest therapy key words, as well as the prize winning work of the 2016 forest therapy experience essay. A word cloud was generated by frequency of nouns and adjectives and from the key words in the web pages, theses, articles, and the forest therapy experience essay. Through interpretation of word frequency, the systemic flow of forest therapy was defined. The results suggest that the source of forest therapy's power was a positive experience of the forest and an improved attitude toward nature as well as forest therapeutic factors. The therapeutic effect is maximized through the forest healing program, leading to physical and mental resilience and resistance; consequently, health and immunity are promoted. From this study, forest therapy is proposed as "a health promotion activity for the psychological, physical, and spiritual resilience of the subjects through various environmental factors of the forest, positive experiences, and attitudes toward the forest."

• Journal of Korea Multimedia Society
• /
• v.23 no.8
• /
• pp.1049-1058
• /
• 2020

'Instagrammable' is a new term which means a photo or a series of pictures are worth posting on Instagram. Since Instagram is an image-oriented social media platform, it is important to give users proper awareness through images in order to be an instagrammable post. In this study, we explored the proper delivery method of messages within instagrammable posts through the use of hashtags(#). Specifically, we paid attention to the use of 'Card News', which involves a series of images that form a short narrative. Hashtags play an important role that they often describe sharing intention of the post, and we found analyzing the use of hashtags in Card News posts is a good indicator of users' Instagram activities. Currently, there are more than 580k posts are found with the search keyword Card News, and the number is increasing. In this study, we collected and analyzed more than 50k hashtags on Instagram to explore how news stories are posted from both the general users and news media accounts. Furthermore, we conducted interviews with journalists to analyze how news media are making use of Instagram as a legitimate place to share news stories with impact.

• Journal of Contemporary Eastern Asia
• /
• v.13 no.2
• /
• pp.15-39
• /
• 2014

This research conducted a before/after naturalistic field experiment, with the early Arab Spring as the treatment. Compared to before the early Arab Spring, after the observation period the associations became stronger among the Web terms: 'Jihad, Sharia, innovation, democracy and civil society.' The Western concept of civil society transformed into a central Islamist ideological component. At another level, the inter-nation network based on Jihad-weighted Web hyperlinks between pairs of 46 Muslim Majority (MM) nations found Iran in one of the top two positions of flow betweenness centrality, a measure of network power, both before and after early Arab Spring. In contrast, Somalia, UAE, Egypt, Libya, and Sudan increased most in network flow betweenness centrality. The MM 'Jihad'-centric word co-occurrence network more than tripled in size, and the semantic structure more became entropic. This media "cloud" perhaps billowed as Islamist groups changed their material-level relationships and the corresponding media representations of Jihad among them changed after early Arab Spring. Future research could investigate various rival explanations for this naturalistic field experiment's findings.