• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.119-133
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• 2020

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.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.163-171
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• 2021

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.

• Informatization Policy
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• v.29 no.3
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• pp.82-104
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• 2022

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.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.2
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• pp.123-136
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• 2023

Upon examining land prices in the eastern district of Gyeongseong, it was observed that there were variations in land prices between the northern and southern areas, with the central part being densely populated with modern facilities such as hospitals, schools, and research institutions. As a result, the eastern district of Gyeongseong was further divided into specific sub-areas, namely the northeastern and southeastern, for a more detailed analysis of the land market in each area. In the northeastern area, factors such as distance from the central area and proximity to planned roads were found to have an impact on land prices. On the other hand, in the southeastern area, the distance between the main road, whice were IHyun Road and Jongro, was identified as a significant influencer of land prices. Therefore, the northeastern area exhibited characteristics of a hinterland, influenced by the concentration of major facilities in the central area, while the southeastern area had a strong commercial orientation, largely shaped by the influence of Jongro as a bustling commercial district. This study is significant in that it sheds light on certain aspects of the modern land market by demonstrating that factors such as accessibility to roads and anchor facilities, as well as the segmentation of the land market, were also influential in the land market a century ago.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.81-97
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• 2022

This paper's purpose is to get hold of the recent research trend by analyzing the variables uesd in startups related papers. The startups related papers in this paper are the papers which include 'startups' in the title of the registered papers from the year 2013 to the year 2020. This study's analysis methods are text-mining of all variables and text-network analysis of affected variables. Visualizing tool for network analysis is Gephi. The result of variables' analysis is as follows. First, independent variables consist mainly of variables about startups' internal factors and outside environment, but due to startups' features like early stage company's features, innovative features, most of variables are about enterprise internal competitiveness, marketing 4P strategy, entrepreneurship, coopreation method, transformational leadership, enterprise features, lean startup strategy, enterprise internal communication, value orientation, task conflict, relationship conflict, knowledge sharing, etc. Second, dependent variables are mainly about outcome, and are classified into financial performance and non-financial performance by overall concept. In other words, startups related papers have higher interest in non-financial performance, like management performance, team performance, SCM performance as well as financial performance like sales quantity owing to startups' immaturity in getting good financial performance. Through this study we can find out as follows. Although there are not many officially registered papers dealing with startups, those papers include various themes about stratups. For example, there are trendy themes like lean startups strategy, crowdfunding, influencer and accelerator, etc.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.199-209
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• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.