• Title/Summary/Keyword: CONCOR

Search Result 125, Processing Time 0.027 seconds

A Study on the Purchasing Factors of Color Cosmetics Using Big Data: Focusing on Topic Modeling and Concor Analysis (빅데이터를 활용한 색조화장품의 구매 요인에 관한 연구: 토픽모델링과 Concor 분석을 중심으로)

  • Eun-Hee Lee;Seung- Hee Bae
    • Journal of the Korean Applied Science and Technology
    • /
    • v.40 no.4
    • /
    • pp.724-732
    • /
    • 2023
  • In this study, we tried to analyze the characteristics of color cosmetics information search and the major information of interest in the color cosmetics market after COVID-19 shown in the text mining analysis results by collecting data on online interest information of consumers in the color cosmetics market after COVID-19. In the empirical analysis, text mining was performed on all documents such as news, blogs, cafes, and web pages, including the word "color cosmetics". As a result of the analysis, online information searches for color cosmetics after COVID-19 were mainly focused on purchase information, information on skin and mask-related makeup methods, and major topics such as interest brands and event information. As a result, post-COVID-19 color cosmetics buyers will become more sensitive to purchase information such as product value, safety, price benefits, and store information through active online information search, so a response strategy is required.

Analysis of YouTube Viewers' Characteristics and Responses to Virtual Idols (버추얼 아이돌에 대한 유튜브 시청자 특성과 반응 분석)

  • JeongYoon Kang;Choonsung Shin;Hieyong Jeong
    • Journal of Information Technology Services
    • /
    • v.23 no.3
    • /
    • pp.103-118
    • /
    • 2024
  • Due to the advancement of virtual reality technology, virtual idols are widely used in industrial and cultural content industries. However, it is difficult to utilize virtual idols' social perceptions because they are not properly understood. Therefore, this paper collected and analyzed YouTube comments to identify differences about social perception through comparative analysis between virtual idols and general idols. The dataset was constructed by crawling comments from music videos with more than 10 million views of virtual idols and more than 10,000 comments. Keyword frequency and TF-IDF values were derived from the collected dataset, and the connection centrality CONCOR cluster was analyzed with a semantic network using the UCINET program. As a result of the analysis, it was found that virtual idols frequently used keywords such as "person," "quality," "character," "reality," "animation," while reactions and perceptions were derived from general idols. Based on the results of this analysis, it was found that while general idols are mainly evaluated with their appearance and cultural factors, social perceptions of virtual idols' values are mixed with evaluations of cultural factors such as "song," "voice," and "choreography," focusing on technical factors such as "people," "quality," "character," and "animation." However, keywords such as "song," "voice," "choreography," and "music" are included in the top 30 like regular idols and appear in the same cluster, suggesting that virtual idols are gradually shifting away from minority tastes to mainstream culture. This study aims to provide academic and practical implications for the future expansion of the industry and cultural content industry of virtual idols by grasping the social perception of virtual idols.

Designing the Museum Gamification System

  • Jeon, Se-won;Moon, Seok-Jae;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.14 no.2
    • /
    • pp.219-224
    • /
    • 2022
  • We identified the correlation between museums, gamification, and viewers based on the results of keyword correlation analysis, designing the museum gamification system. By applying gamification to the museum through big data CONCOR analysis, it was found that viewers had fun watching it through direct experiences and experiences. In this study, we propose a system that directly selects the story desired by the viewer and serves the game suitable for the theme of the museum they visited. In addition, the system proposed in this paper organized a story algorithm so that viewers can directly select the difficulty level based on the story and play personalized games. We collected existing museum information and designed to enable games of various stories suitable for the museum's theme, and based on this, it was applied to the museum gamification app. Moreover, in order to further enhance the immersion of museum viewing. We have been designed and applied based on Virtual Reality (VR).

A study on changes in domestic tourism trends using social big data analysis - Comparison before and after COVID19 -

  • Yoo, Kyoung-mi;Choi, Youn-hee
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.14 no.2
    • /
    • pp.98-108
    • /
    • 2022
  • In this study, social network analysis was performed to compare and analyze changes in domestic tourism trends before and after the outbreak of COVID-19 in a situation where the damage to the tourism industry due to COVID-19 is increasing. Using Textom, a big data analysis service, data were collected using the keywords "travel destination" and "travel trend" based on the collection period of 2019 and 2020, when the epidemic spread to the world and became chaotic. After extracting a total of 80 key words through text mining, centrality was analyzed using NetDraw of Ucinet6, and clustered into 4 groups through CONCOR analysis. Through this, we compared and analyzed changes in domestic tourism trends before and after the outbreak of COVID-19, and it is judged to provide basic data for tourism marketing strategies and tourism product development in the post-COVID-19.

Classification System of Fashion Emotion for the Standardization of Data (데이터 표준화를 위한 패션 감성 분류 체계)

  • Park, Nanghee;Choi, Yoonmi
    • Journal of the Korean Society of Clothing and Textiles
    • /
    • v.45 no.6
    • /
    • pp.949-964
    • /
    • 2021
  • Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

A Study on Trends Related to Boryeong Mud Festival Using Tourism Big Data Analysis (관광 빅데이터 분석을 활용한 보령머드축제 관련 동향 탐색 연구)

  • Han Jangheon
    • Journal of Korea Society of Digital Industry and Information Management
    • /
    • v.19 no.3
    • /
    • pp.165-175
    • /
    • 2023
  • Boryeong Mud Festival has become a representative local festival that both domestic and foreign tourists can enjoy together. In addition, it is one of the usual hands-on marine festivals in Korea that can be enjoyed with one mind at the Boryeong Mud Festival, regardless of race, age, and language. This study explored the overall perception and trends of the Boryeong Mud Festival using big data extracted online from the Boryeong Mud Festival. First, keywords such as Chungnam, hosting, summer, reporter, experience, opening ceremony, performance, operation, news, tourist, opening, event, and festival were frequently exposed online. Second, due to centrality analysis, the centrality of festival experience programs and performances, opening ceremonies, and Boryeong mayor was high. Third, due to the CONCOR analysis, five clusters of meaningful keywords related to the Boryeong Mud Festival were formed.

A Study on Gamification Consumer Perception Analysis Using Big Data

  • Se-won Jeon;Youn Ju Ahn;Gi-Hwan Ryu
    • International Journal of Advanced Culture Technology
    • /
    • v.11 no.3
    • /
    • pp.332-337
    • /
    • 2023
  • The purpose of the study was to analyze consumers' perceptions of gamification. Based on the analyzed data, we would like to provide data by systematically organizing the concept, game elements, and mechanisms of gamification. Recently, gamification can be easily found around medical care, corporate marketing, and education. This study collected keywords from social media portal sites Naver, Daum, and Google from 2018 to 2023 using TEXTOM, a social media analysis tool. In this study, data were analyzed using text mining, semantic network analysis, and CONCOR analysis methods. Based on the collected data, we looked at the relevance and clusters related to gamification. The clusters were divided into a total of four clusters: 'Awareness of Gamification', 'Gamification Program', 'Future Technology of Gamification', and 'Use of Gamification'. Through social media analysis, we want to investigate and identify consumers' perceptions of gamification use, and check market and consumer perceptions to make up for the shortcomings. Through this, we intend to develop a plan to utilize gamification.

Proposed a consulting chatbot service for restaurant start-ups using social media big data

  • Jong-Hyun Park;Yang-Ja Bae;Jun-Ho Park;Ki-Hwan Ryu
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.15 no.3
    • /
    • pp.1-7
    • /
    • 2023
  • Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.

Study on Promotion of ESG Tourism in Bhutan through Big Data Analysis - Focusing on comparison with ESG Tourism status in Korea-

  • Min Kyeong Kim
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.15 no.2
    • /
    • pp.39-48
    • /
    • 2023
  • The purpose of this study is to revitalize ESG tourism in Bhutan by comparing and analyzing the ESG tourism status in Bhutan and the ESG tourism status in Korea. Big data analysis using text mining was performed by selecting "Bhutan ESG Tourism" and "Korea ESG Tourism" as keywords. The top 30 keywords were extracted through word purification, and based on this, data visualization was conducted through network analysis and Concor analysis between each keyword. As a result of the analysis, it was confirmed that Bhutan, unlike Korea, did not utilize it even though it had elements to incorporate ESG and the tourism industry into the country itself. As a result, since it is necessary to combine ESG elements owned by Bhutan and combine them with the tourism industry, we would like to suggest the direction of combining ESG and the tourism industry through this study.

A Sustainable Tourism Study in Underdeveloped Areas Using Big Data Analysis Techniques

  • Hyun-Seok Kim;Sang-Hak Lee;Gi-Hwan Ryu
    • International Journal of Internet, Broadcasting and Communication
    • /
    • v.16 no.2
    • /
    • pp.112-118
    • /
    • 2024
  • We Design The problem of underdeveloped areas is emerging as a social problem. Industrialization drove the population to the cities, creating underdeveloped areas. Underdeveloped areas are causing social problems such as population decline and aging. It is necessary to study the continuous tourism development of underdeveloped areas through development and improvement projects. Using social media big data to investigate keywords in underdeveloped areas and see the connection between keywords. The purpose of this study was to conduct core research divided by type and to investigate the keywords of tourism in underdeveloped areas through concor analysis of underdeveloped areas. As a result of the study, keywords were connected for each type of redevelopment, regional development, regional economy, and underdeveloped areas. Through this, the keywords for sustainable tourism in underdeveloped areas were identified. It is hoped that this study will develop sustainable tourism for the keywords of underdeveloped areas.