• Knowledge Management Research
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• v.22 no.4
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• pp.217-235
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• 2021

As 49% of the world's population uses social media platforms, communication and content sharing within social media are becoming more active than ever. In this environmental base, the one-person media market grew rapidly and formed public opinion, creating a new trend called sell-sumer. This study defined new types of influencers by product category by analyzing the subject concentration of the commercial/non-commercial keywords of influencers and the impact of the ratio of commercial postings on sales. It is hoped that influencers working within social media will be helpful to new sales strategies that are transformed into sell-sumers. The method of this study classifies influencers' commercial/non-commercial posts using Python, performs text mining using KoNLPy, and calculates similarity between FastText-based words. As a result, it has been confirmed that the higher the keyword theme concentration of the influencer's commercial posting, the higher the sales. In addition, it was confirmed through the cluster analysis that the influencer types for each product category were classified into four types and that there was a significant difference between groups according to sales. In other words, the implications of this study may suggest empirical solutions of social media sales strategies for influencers working on social media and marketers who want to use them as marketing tools.

• Asia Marketing Journal
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• v.13 no.3
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• pp.135-161
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• 2011

Social commerce is a more recent phenomenon and growing in number and size with the diffusion of social networking services. But it has not been studied as extensively. The purpose of this study is to investigate consumers' social commerce usage intention empirically. Using the theory of reasoned action suggested by Fishbein and Ajzen(1975), this study tests that perceived value created by social commerce affects social commerce usage intention. In this study, authors e identify to the conception of perceived value as a multidimensional construct, economic, psychology, and time value. This study is to analyze the effects of the value perceived by the consumer on attitude toward social commerce and the effects of the attitude and subjective norm on social commerce usage intention. Additionally, we examine the moderating role of coupon redemption effort in the relationship between attitude toward social commerce and usage intention. In order to evaluative the validity of the model, 258 questionnaires were collected from college students who frequently use SNS and accept new trend and technology using internet survey. All the instrument items used in this study were adapted from previous research and the data were analyzed using SPSS 18 and AMOS 7. This study proposed several hypotheses and conducted an experiment to test these hypotheses. Based on the data analysis results, it was found that economic and psychology value has significant effects on attitude toward the social commerce but time value had not the effect on attitude toward the social commerce. And the present study has also shown that both attitude toward the social commerce and subjective norm significantly influenced usage intention. This finding suggests that the theory of reasoned action effectively explains the social commerce usage intention. The result regarding the moderating effect of the coupon redemption effort has shown that the attitude toward social commerce and usage intention is moderated by consumer perception about coupon redemption.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.139-152
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• 2015

One of the most latest trends in today's marketing practice is to create branded contents for interacting with online consumers. Marketers are increasingly adopting behind-the-scene contents which disclose a brand's backstage information in their contents marketing efforts. The current study conceptualizes this behind-the-scene storytelling based on dramaturgical theory and investigates its impacts on consumer responses. The study also examines how consumers advertising skepticism level would influence on the evaluation of branded contents. In addition, the moderating role of advertising skepticism in evaluating brand's backstage information is investigated. The findings suggests that consumers who are exposed to brand's backstage indicate greater information attitude, brand attitude, and purchase intention than those who are not exposed to brand's backstage. Also consumers who have lower advertising skepticism evaluated branded contents more positively than high ad skepticism consumers. Lastly, the moderating role of advertising skepticism on the impact of brand's backstage disclosure is reported.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.549-555
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• 2016

This paper tries to find the implications applied to art institutions of Korea by analyzing what the content and consequences of services of the Cleveland Museum of Art provided after the Internet of Things adoption in the theoretical perspectives strengthening service marketing through the Internet of Things increases visits and participation in the museum. For analysis, journal articles, statistics, and government press releases, news articles, web pages, web page articles are collected. The results are first, the application of digital and social media is positive in visit to the museum and monetization. Second, the introduction of the Internet of Things will enhance the museum's 'Education', 'Accessibility', 'Communications' services, as well as significantly increase on and offline participation by activating experience. Third, technical support from related companies with the support of local government funds is essential to build the system. Consequently, in order to enable the participation of the spectators in the galleries it is proposed aggressive adoption of such digital technology in domestic barren market of Internet of Things.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.133-144
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• 2014

As the Internet and smartphones prevail, this study investigated the purchasing factors of a new beauty marketing method, the social commerce, and verified the relationship of such purchasing factors to consumer satisfaction and repurchasing intentions. In order to verify the validity of purchasing factors, five sub-factors, such as service, price, interaction, convenience, and interest were classified, while consumer satisfaction and repurchasing intentions are grouped into one factor, using data about 20-39 years old. According to results of this study, purchasing factors in the beauty service markets through social commerce that had effects on the consumer satisfaction were price, service, convenience, and interest, but no relationship was found with interaction. We can predict that consumers buy not based on community activities among buyers or purchasing comments of others, but rather his/her own subjective thoughts and opinions about the services. As the result of repurchasing intention according to purchasing factors, affecting sub-factors were price, service, and convenience. Repurchasing intention is an positive response that reflects satisfactions. Since low price, satisfaction on the service, and convenience for busy modern people should be met, repurchasing intentions are not affected by interest, but rather systematic and professional service. Also, higher satisfaction on service raises repurchasing intention. In this study, it is clear that not only purchasing factors through social-commerce effect the satisfaction and the repurchasing intention, but also consumer satisfaction mediates partly purchasing factors and the repurchasing intention. And as sub-factors of purchasing factors, price, service, or convenience are more important to the consumer satisfaction than community or replies activities. Thus differentiated and professional customer service, the establishment and enhancement of trendy marketing should improve long term repurchasing intentions. This will lead to the increasing revenue of personal-shop and the developments of beauty markets, so strengthening product sourcing and promotion suitable for mobile shoppers are essential.

• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.389-397
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• 2019

As the usage of e-cigarettes and its effects on health harms receive attentions, the debate over regulating e-cigarette industry's' social media marketing has been heated. While the industry has aggressively employed social media marketing such as YouTube, little research has examined what kinds of e-cigarette information is delivered to Korean viewers through YouTube. This study investigated the presence of product-related information and health harm information in the videos, and the characteristics of YouTube creators. The proportion of female creators was smaller than male creators, but more than female smoking rates. The results showed that product-related information such as taste, design and convenience was mentioned more than half the videos, but health ham was mentioned less. Videos which mentioned convenience and design tended to not mention health harm. These results could be used to support the current regulation approach over e-cigarette YouTube marketing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• The Journal of Bigdata
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• v.2 no.2
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• pp.57-66
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• 2017

Companies has been investing enormous resources in promotion as the market keeps changing rapidly. Therefore, there are growing needs to measure the impact of a promotion on revenue growth. To investigate the effect of promotion in franchise food service industry, this study empirically analyzed text data from Twitter, one of the dominant social network services. Our findings show that a gap between promotions, promotion duration, and season have a significant influence on a volume of twitter buzz, which represents a promotion effect in our study. Next, we tried to analyze the reason why those factors were related to the promotion effect. Finally, we suggested promotion strategies related to each influential factor depending on types of business in food service industry.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.65-72
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• 2020

Big data analysis is widely used in applications such as finance and communication, whose market size is growing rapidly every year. Nevertheless, it is rarely used by SMEs (small and medium-sized enterprises) since the existing services are not fully customized for them while being offered at high price. To resolve this, we develop and propose a new platform to provide big data analysis services specialized for SMEs in this paper. First, we compare existing work discussing social big data analysis, and extract service features necessary to help their marketing effectively. Then, we present a prototype system implementing the extracted features, and discuss technical issues needed to develop a complete system which are obtained from the prototype implementation.