• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.83-99
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• 2012

The present study surveyed 225 undergraduates to examine their social media use behaviors and their perceptions of usefulness, trustworthiness, and privacy of social media for seeking and sharing health information. 151 respondents reported using social media for health information while 74 reported not using it for health matters. Results show that the most popular medium were social Q&As, followed by blogs and social networking sites. Age, gender, school year, and the presence of a health problem were associated with the social media use behaviors. This study suggests the potential of social media as a desired channel for providing health information to undergraduates.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.427-428
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• 2013

본 논문에서는 정보화에 취약한 농가의 약점을 보완할 수 있는 정보포털 시스템을 설계하여 중소규모의 농가 쇼핑몰, 블로그 등을 스토리텔링과 결합하여 온라인으로 홍보가 가능하도록 하였다. 농산물 홍보용 허브 플랫폼은 농가들이 운영하는 수없이 많은 쇼핑몰과 농 특산물을 홍보하기 위한 마케팅채널과 직접 자신의 농산물을 소개할 수 있는 채널을 구축하여 소비자와 생산자 실시간 온라인 대화채널 구축을 통한 소통 공간 조성 및 신뢰성을 확보할 수 있다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.307-314
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• 2016

This study empirically validate the impacts of WOM information characteristics on the WOM effect in accordance with SNS media due to the increased the WOM role under SNS. The key results showed that the more vivid, negative, and objective WOM information was, the more positive impacts on the intention to adopt information. In addition, the intention to adopt information had a positive impact on the re-WOM intention. Second, there was no significant difference between Facebook and Blog groups regarding the impacts of the WOM information characteristics on the WOM effect. This can be inferred from the fact that consumers recognize all SNS media as a single online medium regardless of their characteristics in the process of accepting and spreading information. Based on these results, this research drew the following implications. It conceptualized the information characteristics factors that influence the online information acceptance process and the relationship with WOM effects by focusing on SNS and high-tech products that are rapidly emerging. This study is also significant because it attempted to expand the characteristics of WOM information and WOM effects to Facebook and blogs, which are SNS media, and proposed a future research direction.

• The Journal of Bigdata
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• v.6 no.2
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• pp.169-179
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• 2021

Consumers' food consumption behavior is likely to be affected not only by structured data such as consumer panel data but also by unstructured data such as mass media and social media. In this study, a deep learning-based consumption prediction model is generated and verified for the fusion data set linking structured data and unstructured data related to food consumption. The results of the study showed that model accuracy was improved when combining structured data and unstructured data. In addition, unstructured data were found to improve model predictability. As a result of using the SHAP technique to identify the importance of variables, it was found that variables related to blog and video data were on the top list and had a positive correlation with the amount of paprika purchased. In addition, according to the experimental results, it was confirmed that the machine learning model showed higher accuracy than the deep learning model and could be an efficient alternative to the existing time series analysis modeling.

• Asia Marketing Journal
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• v.11 no.2
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• pp.73-96
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• 2009

In this paper, authors focused on the difference between successful and unsuccessful items in terms of the innovation and imitation parameters of Bass diffusion model. Each item was scraped by members directly from the minihompies they visit. Top 50 items in terms of total number of adoption are classified as successful items and the 50 items whose total number of adoption was just below the average are classified as unsuccessful items. In particular, authors are interested in investigating the role of influentials in the diffusion process. Influentials are defined as those people whose network centrality (Indegree, Outdegree, and Betweeness centrality) was larger than the mean centrality in their social network. Figure 1 shows the plots of number of scraping, cumulative scraping, indegree, outdegree and betweenness of the people who scraped the most popular item among 100 items.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.514-523
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• 2021

Recently, the proliferation of mobile simple payment services has been increasingly affecting people's lives. In addition, the increase in research from both China and Korea shows that the continuous development of simple mobile payment services will be very important in the future. The blog posts mentioning Kakao Pay and Alipay were collected, and keyword analysis was performed to investigate differences in consumers' responses to Kakao Pay and Alipay on social media. The frequency of keywords for each part of speech and the frequency of co-occurred words mentioned in one sentence were analyzed. Specifically, common words that appear in both Kakao Pay and Alipay blogs were extracted. The cooccurred words were analyzed to examine how different reactions were made on the same subject. As a result of the analysis, there were concerns among consumers about the trust of Kakao Pay and Alipay's benefits. For a mobile payment service to become competitive, it is necessary to add various additional services or solve security problems.

• Management & Information Systems Review
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• v.29 no.4
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• pp.143-167
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• 2010

Diverse research topics relating to Social Network Services (SNS) such as, social affective factors in relationships among internet users, social capital value of SNS, comparing attributes why users are intending to participate in SNS, user's lifestyle and their preferences, and the exploratory seeking potential of SNS as a social capital need to be focused on. However, these researches that have been undertaken only consider facts at a particular period of the changing computing environment. In accordance with this indispensability, the integrated view on what technical, social and business characteristics and attributes need to be acknowledged. The purpose of this study is to analyze the evolving attributes and characteristics of SNS from Web 1.0 to Mobile web 2.0 through the Web 2.0 and Mobile 1.0 period. Based on the relevant literature, the attributes that drive the changing technological, social and business aspects of SNS have been developed and analyzed. This exploratory study analyzed major attributes and relationships between SNS and users by changing the paradigms which represented each period. It classified and chronicled each period by representing paradigms and deducted the attributes by considering three aspects such as technological, social and business administration. The major findings of this study are, firstly, the web based computing environment has been changed into the platform attribute for users in the aspect of technology. Users can only read, listen and view information through the web site in the early stages, but now it is possible that users can create, modify and distribute all kinds of information. Secondly, the few knowledge producers of web services have been changed into a collective intelligence by groups of people in the aspect of society. Information authority has been distributed and there is no limit to its spread. Many businesses recognized the potential of the SNS and they are considering how to utilize these advantages toward channel of promotion and marketing. Thirdly, the conventional marketing channel has been changed into oral transmission by using SNS. The market of innovative mobile technology such as smart phones, which provide convenience and access-ability toward customers, has been enlarged. New opportunities to build friendly relationship between business and customers as a new marketing chance have been created. Finally, the role of the consumer has been changed into the leading role of a prosumer. Users can create, modify and distribute information, and are performing the dual role of customer and producer.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.724-732
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• 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.