The Journal of the Convergence on Culture Technology
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v.9
no.3
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pp.81-94
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2023
The study aims to compare and analyze the social network structures of Qatar Airways,s Singapore Airlines, Emirates Airlines, and ANA Airlines, recording the top 1 to 4, and Korean Air in ninth by Skytrax's airline evaluations in 2022. This study uses NodeXL, a social network analysis program, to analyze the social networks of 5 airlines, Vertex, Unique Edges, Single-Vertex Connected Components, Maximum Geodesic Distance, Average Geodesic Distance, Average Degree Centrality, Average Closeness Centrality, and Average Betweenness Centrality as indicators to compare the differences in these social networks of the airlines. As a result, Singapore's social network has a better network structure than the other airlines' social networks in terms of sharing information and transmitting resources. In addition, Qatar Airways and Singapore Airlines are superior to the other airlines in playing roles and powers of influencers who affect the flow of information and resources and the interaction within the airline's social network. The study suggests some implications to enhance the usefulness of social networks for marketing.
Recently, the desire for low body weight, which is an abnormal weight construct along with obesity, has become an evident and serious problem in teenagers. In Korea, the desire for low weight is not perceived as an important problem, but it is rapidly expanding relative to the physical changes and developmental issues teenagers experience. The social atmosphere presented through mass media is the key influencer for the increasing low weight occurrence in teenagers. Because thoughts about beauty have changed among people, and since there is apparent blind interest in slim body shape and appearance, already low-weight individuals are attempting to lose weight along with obese persons. Thus, we consider it necessary to guide teenagers toward having correct perceptions with regard to weight and their own body shape, and that a healthy and appropriate weight is beautiful. Therefore, for this study, we investigated body perception, abnormal weight, attitude toward weight control, and factors related to eating behavior among teenage girls, who are considered the at risk group for overt body weight control behavior. Based on this, we have attempted to set in motion a systematic and active nutrition education program that will allow us to increase body satisfaction by educating on nutritional issues related to development, and ultimately, implant healthy body shape perceptions.
This study investigates the perception and adoption of ChatGPT (a large language model (LLM)-based chatbot created by OpenAI) among Korean users and assesses its potential as the next disruptive innovation. Drawing on previous literature, the study proposes perceived intelligence and perceived anthropomorphism as key differentiating factors of ChatGPT from earlier AI-based chatbots. Four individual motives (i.e., perceived usefulness, ease of use, enjoyment, and trust) and two societal motives (social influence and AI anxiety) were identified as antecedents of ChatGPT acceptance. A survey was conducted within two Korean online communities related to artificial intelligence, the findings of which confirm that ChatGPT is being used for both utilitarian and hedonic purposes, and that perceived usefulness and enjoyment positively impact the behavioral intention to adopt the chatbot. However, unlike prior expectations, perceived ease-of-use was not shown to exert significant influence on behavioral intention. Moreover, trust was not found to be a significant influencer to behavioral intention, and while social influence played a substantial role in adoption intention and perceived usefulness, AI anxiety did not show a significant effect. The study confirmed that perceived intelligence and perceived anthropomorphism are constructs that influence the individual factors that influence behavioral intention to adopt and highlights the need for future research to deconstruct and explore the factors that make ChatGPT "enjoyable" and "easy to use" and to better understand its potential as a disruptive technology. Service developers and LLM providers are advised to design user-centric applications, focus on user-friendliness, acknowledge that building trust takes time, and recognize the role of social influence in adoption.
This study classifies the success of creators and YouTubers who have created channels on YouTube recently, which is the most influential digital platform. Based on the actual information disclosure of YouTubers who are in the field of science and technology category, video upload cycle, video length, number of selectable multilingual subtitles, and information from other social network channels that are being operated, the success of YouTubers using machine learning was classified and analyzed, which is the closest to the YouTube revenue structure. Our findings showed that neural network algorithm provided the best performance to predict the success or failure of YouTubers. In addition, our five factors contributed to improve the performance of the classification. This study has implications in suggesting various approaches to new individual entrepreneurs who want to start YouTube, influencers who are currently operating YouTube, and companies who want to utilize these digital platforms. We discuss the future direction of utilizing digital platforms.
As the COVID-19 pandemic confirmed the culture of non-face-to-face consumption. In retail commerce, the 'live commerce' market, where sales are made by communicating with customers in the form of live streaming broadcasts, has grown rapidly. Although previous studies have consistently confirmed the phenomenon of "influencers" in society and culture, there is a lack of research on the "sales expertise" of live commerce broadcasters such as Wang Hong in China. In China, "Wang Hong" is short for "Wang Luo Hong Ren", a combination of "Wang Luo", which means the Internet, and "Hong Ren", which means star, and refers to a person who is popular through social platforms and is gaining popularity from many fans. Therefore, this study focuses on Wang Hong's developing "selling expertise" and examines it from the perspective of a shopping curator. In particular, we applied Harold Jarche(2011)'s "Seek-Sense-Share" model to influencers to verify their influence on trust and purchase intention in live commerce. Furthermore, we analyzed the differences between Korea and China.A survey was conducted among live commerce users in Korea and China, and a total of 228 questionnaires were used in the final analysis. Basic statistical analysis was conducted using SPSS and hypotheses were tested using PLS 3.0. The results of the hypothesis testing showed that influencers' curatorial competence "Seek-Sense-Share" had a significant effect on trust, and trust had a positive effect on purchase intention. In addition, there is a significant difference between Korean and Chinese consumers in this relationship.
Purpose - Media is a significant distributional channel in sport. In terms of determining the influencer in building sport media contents, recent sport media studies have employed agenda-setting theory, assuming media itself as the agenda provider. In a real-world situation, however, sports stars have been deemed key factor determining distribution contents in sport. The starting point of this study is the "tacit premise" of agenda-setting theory. Given the agenda-setting theory, the current study attempted to explore the function of sport stars as an agenda provider, which is a key determinant of sport distribution. Research design, data, and methodology - This study has reviewed articles of Yuna Kim, Sang-hwa Lee, and Hyun-jin Ryu from daily newspapers including as dong-a ilbo and joongang ilbo (2013 to 2017). The study collected data, portable document format (PDF), from the online archive of dong-a ilbo and joongang ilbo. We coded the length of the article, the frequency, the size of the picture, and the structural form of the article. Inter-coder reliability was compared with data previously investigated by the researcher. Inter-coder reliabilities for study 1 and 2 was .89 and .85. To examine hypotheses, descriptive analysis, correlations, and cross-tap analysis were performed. Results - The results partially supported the hypotheses proposing the significant role of sports stars as the agenda setters in distributing sport media contents. In specific, the study found that the number of articles about sports stars prevailed the number of articles about regular athletes. Besides, studies found that the use of photos was more frequent in articles of sports starts than that of regular athletes. In sports newspaper articles, featured story articles were used more than straight-articles for news relating to sports stars. Also, sports newspaper of sports stars contained more information associated within an event rather than outside of an event. Conclusions - In sports journalism, this study challenges the current theory that the media affects the composition and the content of sports coverages. As the principle of the agenda-setting of sports media, the influence of sports stars must be continuously studied along with a follow-up study.
Recently, as famous YouTubers produce and broadcast videos that receive sponsorship and advertising such as indirect advertising (PPL), a so-called 'back advertising' controversy continues, and not only famous YouTubers but also entertainers are caught up in the issue. It is causing confusion among the public in Korea. This study attempts to find out the public's reaction before and after the controversy of 'back advertising' by YouTubers through comment analysis. Specifically, among text analysis using R programs, we intend to analyze the issue through various methods such as word cloud, qgraph analysis, LDA, and word2vec analysis, a deep learning technique. The target of the analysis was to analyze the channels of three YouTubers who belonged to the controversy of the 'back advertising' YouTuber and uploaded the 'Apology video'. The 5 most recent videos of Muk-bang YouTuber Moon Bok-hee, who has a similar content disposition to SussTV's Han Hye-yeon stylist, which was controversial, and Yang Pang, a YouTuber who showed various contents (August 09, 2020) Criterion and her first 5 videos uploaded were reviewed. As a result of the study, most of the comments that showed positive reactions before the controversy, but after the controversy, it was found that negative reactions accounted for most of the comments. Therefore, this study examines the degree of change of the public about influencers through comments after the controversy over 'back advertising' through various analysis using R program. This research also devises various measures to prevent the occurrence of back advertising of influencers in the future.
The purpose of this study is to examine the current operation condition of fashion start-up companies and the characteristics of their founders in Fashion Creative Studio that is one of government programs supporting fashion start-up of rising fashion designer's brands in Korea and one of supporting facilities. For this purpose, this study surveyed 32 fashion start-up companies founders in Busan Fashion Creative Studio and analyzed the data based on the survey. The results are as follows. First of all, 82% of the founders have experience to start their business in 20s and 60% of founders with not more than 3 to 5 years of work experience related to fashion challenge to start a business. Secondly, major distribution channels of the fashion start-up companies are mainly on-line open-market consisting of 36% and SNS is up to 80% as the main promotion method. In addition, exports to China account for 71% of all exports. Lastly, 33% of businesses consider viral marketing by influencer and 50% of them make plan to export their items to East Asia. It is of research significance that this study can suggest the successful direction of establishing and operating fashion start-up companies through making good use of Fashion Creative Studio, the supporting program including facility.
One of the interesting social phenomena in short-form video platforms is the hashtag challenge wherein ordinary users are encouraged to create by imitating short viral videos on a particular theme. Despite the increasing popularity of hashtag challenges, theoretical discussion on related user behavior is still very insufficient. In this study, we attempted to examine the impact of micro-influencers in order to understand users' willingness to participate in hashtag challenges. For this purpose, the para-social interaction theory and imitation behavior literature were adopted as key theoretical basis. In an empirical investigation using 243 survey data from TikTok users, our study found that a user's illusion of intimacy with a micro-influencer (i.e., para-social interaction) had significant positive impact on the intention to participate in a hashtag challenge. This study also showed that the degree of para-social interaction in a short-form video platform was determined by both media content-related factors and media character-related factors (i.e., content attractiveness, physical attractiveness, and attitude homophily). Our work in this study provided significant theoretical and practical implications on how to leverage micro-influencers for the success of hashtag challenges in a short-form video platform.
KIPS Transactions on Software and Data Engineering
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v.12
no.4
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pp.179-188
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2023
Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.
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