• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.71-89
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• 2019

In order to come up with satisfying product and improvement, firms use traditional marketing research methods to obtain consumers' opinions and further try to reflect them. Recently, gathering data from consumer communication platforms like internet and SNS has become popular methods. Meanwhile, with the development of information technology, mobile companies are launching new digital products for children to protect them from harmful content and provide them with necessary functions and information. Among these digital products, Kids Phone, which is a wearable device with safe functions that enable parents to learn childern's location. Kids phone is relatively cheaper and simpler than smartphone but it is noted that there are several problems such as some useless functions and frequent breakdowns. This study analyzes the reviews of Kids phones from domestic mobile companies, identifies the characteristics, strengths and weaknesses of the products, proposes improvement methods strategies for devices and services through SNS consumer analysis. In order to do that customer review data from online shopping malls was gathered and was further analyzed through text mining methods such as TF/IDF, Sentiment Analysis, and network analysis. Customer review data was gathered through crawling Online shopping Mall and Naver Blog/$Caf\acute{e}$. Data analysis and visualization was done using 'R', 'Textom', and 'Python'. Such analysis allowed us to figure out main issues and recent trends regarding kids phones and to suggest possible service improvement strategies based on sentiment analysis.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.69-81
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• 2024

The The purpose of this study is to have a positive impact on the evaluation of the traditional market revitalization project by discussing the business details and implementation process of the commercial district revitalization project in depth. The research method uses practical methods for traditional market revitalization projects. First, the activation method of the place was examined through the concepts of Oldenburg's 'Third Place' and Carr et al.'s 'Five Demands for Public Space' and the theories related to non-face-to-face transactions were examined. The first study case was the commercial district revitalization project of the Cheongju Global Market Development Project(Seongan-gil Street Shopping Mall and Yukgeori traditional Market), which discussed revitalization of open space, revitalization through reproduction, and revitalization through festivals. The revitalization project through representation is a project to install a symbolic sculpture at the estimated location of the 'Namseokgyo' buried in Yukgeori traditional Market. The revitalization through the festival is the Korea Sale Festa, which is a vibrant business due to increased sales at traditional markets and shopping malls and floating population in open spaces. The second study case was the Cultural Tourism Promotion Project(Hanmin traditional Market), which discussed revitalization through the development of local brands and SNS content. In the conclusion, the relationship between the six projects and commercial district revitalization methods was discussed, and policy recommendations were made, mentioning the importance of reflecting regional characteristics in design planning. We hope that this study will be used to positively evaluate the traditional market revitalization project, showing that stakeholders are working hard to produce positive results within institutional limitations.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.573-588
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• 2023

Purpose: This study aimed to examine social networking service (SNS) use and recommended information utilization (SURU) according to the food-related lifestyles (FRLs) of consumers and analyze how the interaction between the FRL and SURU affects the practice of eating alone and visiting restaurants. Methods: Data on 4,624 adults in their 20s to 50s were collected from the 2021 Consumer Behavior Survey for Food. Statistical methods included factor analysis, K-means cluster analysis, the complex samples general linear model, the complex samples Rao-Scott χ² test, and the general linear model. Results: The following three factors were extracted from the FRL data: Convenience pursuit, rational consumption pursuit, and gastronomy pursuit, and the subjects were classified into three groups, namely the rational consumption, convenient gastronomy, and smart gourmet groups. An examination of the difference in SURU according to the FRL showed that the smart gourmet group had the highest score. The result of analyzing the effects of the FRL and SURU on eating alone revealed that both the main effect and the interaction effect were significant (p < 0.01, p < 0.001). The higher the SURU, the higher the frequency of eating alone in the convenience pursuit, and gastronomy pursuit groups. The main and interaction effects of the FRL and SURU on the frequency of eating out were also significant (p < 0.01, p < 0.001). In all the FRL groups, the higher the SURU level, the higher the frequency of visiting restaurants. Specifically, the two groups with convenience and gastronomic tendencies showed a steeper increase. Conclusion: This study provides important basic data for research on consumer behavior related to food SNS, market segmentation of restaurant consumers, and development of marketing strategies using SNS in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.597-603
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• 2022

With the continuation of the pandemic environment, digital transformation is being applied in various fields of the fashion industry. Augmented reality technology is a form of overlapping virtual images on the real world, and as online shopping expands in non-face-to-face environments, the use of augmented reality technology in fashion and beauty fields is affecting consumer satisfaction and sales growth. In this study, the characteristics of augmented reality contents used in the fashion industry following digital transformation were extended to the fields of clothing, accessories, virtual fashion stores, and AR fashion shows to analyze the case characteristics of augmented reality. Augmented reality technology in the fashion industry focuses on promoting clothing and accessory products through SNS or homepage through marketing activities. It is raising positive values such as raising awareness. The range of types of augmented reality used in the future digital fashion environment will continue to expand, and by deriving the usage characteristics of augmented reality technology, it is intended to contribute to presenting a future vision of the fashion industry.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.599-606
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• 2017

'Video Commerce' has grown significantly, and is in the era of so-called V-commerce 2.0. Based on this background, this study focused on the link and the possibility of creating synergy between V-commerce 2.0 content and MCN, and examined the linkage strategy considering its characteristics. In conclusion, first, V-Commerce has evolved into the age of 2.0, centered on the characteristics of content that are oriented towards fun and sympathy, beyond the 1.0 era. Second, V-commerce 2.0 content has the characteristic of replacing the sharing and recommendation based on the nature of SNS networks as promotion and purchase enhancement. Therefore, competitiveness as 'content' is relatively important before 'commerce'. Third, V-commerce 2.0 and MCN industry have a strong connection with each other in terms of securing core competitiveness and creating a new profit model. In order to create the synergy between V-Commerce 2.0 and MCN, we proposed the use of big data to reinforce V-Commerce 2.0 customized content competitiveness, building of storytelling marketing and branding, and enhancement of live performance and interactive communication.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.157-176
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• 2016

For a long time, mobile phone had a sole function of communication. Recently however, abrupt innovations in technology allowed extension of the sphere in mobile phone activities. Development of technology enabled realization of almost computer-like environment even on a very small device. Such advancement yielded several forms of new high-tech devices such as smartphone and tablet PC, which quickly proliferated. Simultaneously with the diffusion of the mobile devices, mobile applications for those devices also prospered and soon became deeply penetrated in consumers' daily lives. Numerous mobile applications have been released in app stores yielding trillions of cumulative downloads. However, a big majority of the applications are disregarded from consumers. Even after the applications are purchased, they do not survive long in consumers' mobile devices and are soon abandoned. Nevertheless, it is imperative for both app developers and app-store operators to understand consumer behaviors and to develop marketing strategies aiming to make sustainable business by first increasing sales of mobile applications and by also designing surviving strategy for applications. Therefore, this research analyzes consumers' mobile application usage behavior in a frame of substitution/supplementary of application categories and several explanatory variables. Considering that consumers of mobile devices use multiple apps simultaneously, this research adopts multivariate probit models to explain mobile application usage behavior and to derive correlation between categories of applications for observing substitution/supplementary of application use. The research adopts several explanatory variables including sociodemographic data, user experiences of purchased applications that reflect future purchasing behavior of paid applications as well as consumer attitudes toward marketing efforts, variables representing consumer attitudes toward rating of the app and those representing consumer attitudes toward app-store promotion efforts (i.e., top developer badge and editor's choice badge). Results of this study can be explained in hedonic and utilitarian framework. Consumers who use hedonic applications, such as those of game and entertainment-related, are of young age with low education level. However, consumers who are old and have received higher education level prefer utilitarian application category such as life, information etc. There are disputable arguments over whether the users of SNS are hedonic or utilitarian. In our results, consumers who are younger and those with higher education level prefer using SNS category applications, which is in a middle of utilitarian and hedonic results. Also, applications that are directly related to tangible assets, such as banking, stock and mobile shopping, are only negatively related to experience of purchasing of paid app, meaning that consumers who put weights on tangible assets do not prefer buying paid application. Regarding categories, most correlations among categories are significantly positive. This is because someone who spend more time on mobile devices tends to use more applications. Game and entertainment category shows significant and positive correlation; however, there exists significantly negative correlation between game and information, as well as game and e-commerce categories of applications. Meanwhile, categories of game and SNS as well as game and finance have shown no significant correlations. This result clearly shows that mobile application usage behavior is quite clearly distinguishable - that the purpose of using mobile devices are polarized into utilitarian and hedonic purpose. This research proves several arguments that can only be explained by second-hand real data, not by survey data, and offers behavioral explanations of mobile application usage in consumers' perspectives. This research also shows substitution/supplementary patterns of consumer application usage, which then explain consumers' mobile application usage behaviors. However, this research has limitations in some points. Classification of categories itself is disputable, for classification is diverged among several studies. Therefore, there is a possibility of change in results depending on the classification. Lastly, although the data are collected in an individual application level, we reduce its observation into an individual level. Further research will be done to resolve these limitations.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.57-79
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• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

• Science of Emotion and Sensibility
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• v.19 no.1
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• pp.111-126
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• 2016

As the marketing value of Facebook advertisements increases, companies seek to create successful Facebook advertisements in order to promote their brands or products. This research aims to identify Facebook advertising factors that influence users' eye movements and attention, and thereby to investigate effective visual elements of Facebook advertising contents. Firstly, we identified two contributing factors influencing users' responses to Facebook advertisements: the formats of advertising contents(Text, Text in Image, and Movie) and the product properties(Involvement, Think/Feel). Based on theoretical reviews, eye tracking tests and surveys were conducted in order to examine how these two factors affect users' responses on Facebook, i.e. visual perception and users' purchasing responses. It was found that there were distinctive patterns of users' visual perceptions and purchasing behavioral responses according to the formats of the advertised contents. Meanwhile, the advertised products' properties influenced only the users' purchasing responses. Finally, the key findings of this research offer helpful guidelines for providers and developers to create effective SNS advertisements.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.67-76
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• 2014

In this study, we investigated opinion leaders' communication activities on Facebook and analyzed the differences of communication patterns on Facebook between Korean and US college students. As a primary source of information, we conducted an online survey to collect data from students currently enrolled at two different universities in US. Additionally, we utilized online survey data previously collected from Korean students. According to our analysis, we found that US male students had more active opinion leadership than Korean male students. Also, opinion leadership of Korean students' was significantly associated with both active and passive communication patterns on Facebook whereas opinion leadership of US students' was significantly associated with passive communication patterns.