• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.305-308
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• 2013

본 연구는 농산물 전자상거래를 이용하는 소비자들의 신뢰와 구매의도에 영향을 미치는 소셜네트워크 특성을 분석함으로써 그동안 상대적으로 소홀했던 농산물 전자상거래 분야의 소셜네트워크 활용 방안 및 구매의도를 개선하기 위한 시사점을 제공하는데 목적이 있다. 본 연구의 목적을 위해 농산물 전자상거래 이용 소비자들을 대상으로 소셜네트워크특성이 신뢰를 매개로 구매의도에 미치는 영향을 분석한 결과 소셜네트워크 특성으로 도출한 교류빈도, 친밀감, 호혜성, 감정의 강도 중 친밀감, 호혜성, 감정의 강도는 신뢰에 정(+)의 영향을 미치는 것으로 나타났으며, 교류빈도는 정(+)의 영향을 미치지 않는 것으로 나타났다. 또한 신뢰는 구매의도에 정(+)의 영향을 미치는 것으로 분석되었다.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.13-27
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• 2019

Social media are used as a tool which is suitable for delivering various images emotionally in the area of fashion. How deeply consumers are led by the brands to be engaged in the brands' SNS, how often they visit SNS and gain information, how much empathy they elicit from visitors with their contents and how continuously brands provide up-to-date information are the important factors to raise consumers' fashion consciousness and draw out their fashion consumption to express themselves. Therefore, this study aims to explore the effect of social media engagement and contents characteristics on fashion consumption tendency and purchase intention. In order to verify the research question, study makes analysis centering on the 2 × 2 × 2 MANCOVA model to draw out results of the differences among groups. As a result of analysis, this study verifies the difference between the effect of social media engagement on purchase intention and the effect of interaction of three variables on fashion consumption propensity and purchase intention and summarizes the implications.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.109-118
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• 2016

As Internet technology further develops, a social networking service (SNS) also develops. But most studies on SNS are not appropriate for business purposes since they mainly focus on personal characteristics. Unlike previous studies, however, this study tries to understand the effect of SNS on performance in the perspective of business. As the result of analysis, SNSE(Social Networking Service Engagement) appears to have positive effect on TMC(Transactive Memory Capability) and PER(Performance), and TMC also seems to affect PER. On the assumption that there should be some parameters between SNSE and PER that earlier studies did not consider, this study has proved that a new way of memories, or TMC, forms the bridge between SNS and PER. It also found out that the time spent on SNS is positively controlled when SNSE affects TMC. These results are different from those of the previous studies arguing that SNS has nothing to do with PER.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.8
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• pp.301-308
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• 2015

SNS is a web-based online platform service supporting the formation of relations between users. SNS users have usually used a desktop or laptop for this purpose so far. However, the number of SNS users is greatly increasing and their access to the web is improving with the spread of smart phones. They share their daily lives with other users through SNSs. We can detect events if we analyze the contents that are left by SNS users, where the individual acts as a sensor. Such analyses have already been attempted by many researchers. In particular, Twitter is used in related spheres in various ways, because it has structural characteristics suitable for detecting events. However, there is a limitation concerning the detection of events and their locations. Thus, we developed a system that can detect the location immediately based on the district mentioned in Twitter. We tested whether the system can function in real time and evaluated its ability to detect events that occurred in reality. We also tried to improve its detection efficiency by removing noise.

• Management & Information Systems Review
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• v.34 no.3
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• pp.231-250
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• 2015

This study is about the effect of interaction and flow of consumers within the company SNS on the consumers' affection. Verification took place through empirical analysis based on the theoretical background. The following is the summary of the research results generated based on the research results. First, correlation between aspect of the motivation for the use of contents and interactivity is as follows. Mutual sense of solidarity (Hypothesis 1-1), influence (Hypothesis 1-2), connectivity (Hypothesis 1-3) and reactivity (Hypothesis 1-4) exerted positive(+) on the interaction. Second, correlation between aspect of the motivation for the use of contents and flow is as follows. Mutual sense of solidarity (Hypothesis 2-1), influence (Hypothesis 2-2) and connectivity (Hypothesis 2-3) exerted positive(+) effect on immersion. Meanwhile, reactivity (Hypothesis 1-4) was not statistically significant when it comes to flow. Third, interaction between contents characteristics and interaction exerted positive(+) positive on the interactivity of entertainingness (Hypothesis 3-1) and informativity (Hypothesis 3-2). Fourth, correlation between contents characteristics and flow was examined, which demonstrated that only informativity (Hypothesis 4-2) exerted positive(+) effect on the immersion. Meanwhile, entertainingness was not statistically significant when it comes to the immersion. Lastly, correlation between interaction, flow and affection is as follows. Correlation between interactivity and flow(Hypothesis 5) was not statistically significant while interactivity(Hypothesis 6) and Flow(Hypothesis 7) exerted positive(+) effect on the affection. This study presents diverse implications and significances to the working level people who use the company SNS based on these results.

• The Journal of Industrial Distribution & Business
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• v.12 no.4
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• pp.35-51
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• 2021

Purpose: As the digital environment has expanded opportunity for consumers to acquire information from social media and social network services(SNS), With this environment, influencer has not only promoted products, but also participated in distribution and influencing on their followers. Despite the increasing interest in influencers, there has not been enough research on the structure of fashion influencer, relationship of immersion and purchase intention. This study examined the effects of fashion influencers' characteristics to the immersion of relationship with followers and purchase intention. Research design, data and methodology: For data collection, a pilot survey and the final survey were conducted. The pilot survey data was conducted to 50 female SNS users following fashion influencers. Based on the pilot tests, questionnaire was revised and the final survey was conducted online from august 22 to September 1, 2019 to female SNS users who have followed fashion influencer. A total of 408 data were collected, and exploratory factor analysis, correlation analysis, and structural equational modeling techniques were employed for the data analyses using AMOS 26.0 and SPSS 26.0. Results: First, five factors were extracted for the fashion influencers' characteristics: interactivity, similarity, reliability, expertise and attractiveness. Second, fashion influences' reliability, expertise, similarity, interactivity have a positive (+) effects on relationship immersion; however, attractiveness has no effect on relationship immersion with followers and fashion influencer. It was also determined that relationship immersion had positive (+) influences on purchase intention. The relationship immersion has been found to have a partially mediated effect and similarity has complete mediated effects between interactivity, reliability, and expertise of fashion influencers and purchasing intentions. In terms of fashion opinion leadership, it was found to have a significant influence on purchase intention only for low fashion leadership groups. Conclusions: The present study found the structural relationships among the influencer characteristics, relationship immersion and purchase intentions to provide framework for succeeding research. This research revealed academic association of intention of purchasing through use of fashion social media and fashion influencer marketing. The results also showed the practical implications that fashion influencers' expertise and reliability perceived by their followers are key determinants to success in influencer marketing.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of Practical Engineering Education
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• v.11 no.2
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• pp.175-180
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• 2019

Existing fashion web sites show only the search results for one type of clothes in items such as tops and bottoms. As the fashion market grows, consumers are demanding a platform to find a variety of fashion information. To solve this problem, we devised the idea of linking image classification through deep learning with a website and integrating SNS functions. User uploads their own image to the web site and uses the deep learning server to identify, classify and store the image's characteristics. Users can use the stored information to search for the images in various combinations. In addition, communication between users can be actively performed through the SNS function. Through this, the plan to solve the problem of existing fashion-related sites was prepared.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.15-26
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• 2018

This study focused on the difference of the volume of sanitory pad issue and The aim of this study is to explore the relationship between the characteristics of SNS and the diffusion of issue in the process of crisis issue. SNS is categorized into communication diffusion, communication restriction,, diffusion, restriction base on the media interactivity and the user interactivity, In case of Twitter, media interactivity is low and user interactivity is low. In case of Youtube, media interactivity and user interactivity are all high. Crisiss issue is interactively diffused via Youtube compared to via Twitter. There was a negative public opinion in social media even if the government and the manufacturer said that there was no harm in the sanitary goods. In conclusion, this study highlights the importance of social media environment in the diffusion of information. The government prepared for the use of SNS in crisis because there was a negative opinion on the government and the manufacturer via SNS.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.2
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• pp.183-203
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• 2023

This study was conducted to analyze the characteristics of the artificial intelligence chatbot service of the library and compare the usability of the chatbot service applied to the library, and to propose a plan to improve the usability of the artificial intelligence chatbot service in the library. In order to achieve this research purpose, usability comparison factors were extracted through previous studies on the usability evaluation of artificial intelligence chatbot services, and based on case studies, artificial intelligence chatbot services applied to libraries were classified into their own website-based and SNS-based chatbot services according to the platform. Experiments, questionnaires, and interviews were conducted to evaluate the usability of website-based and SNS-based chatbot services applied to the library. Based on the results of the usability evaluation, implications and improvement plans for the artificial intelligence chatbot service of the library were derived.