• The Journal of Industrial Distribution & Business
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• v.10 no.8
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• pp.7-15
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• 2019

Purpose - This study aims to examine the influence of social network service (SNS) on the brand image of infant food products; highlight the effects of brand image on the purchasing and word-of-mouth intention; and explore the effects of the purchasing intention on the word-of-mouth intention. Research design, data, and methodology - Based on previous studies, it was found that the fundamental SNS characteristics for infant food products are reliability, interactivity, and informative. Using AMOS 22.0 and structural equation modeling (SEM), 288 questionnaires were surveyed as a statistical method for examining the proposed hypotheses. Results - The analysis shows that reliability and informative have significant impacts on brand image, whereas interactivity does not. Again, the effect of brand image of infant food products on the purchase and word-of-mouth intention is statistically significant. However, the results differ across the "working housewife" and the "full-time housewife" groups. The connection between reliability and brand image was found to be statistically significant in this study. Conclusions - This study analyzes the effects of SNS characteristics on the brand image of infant food products and the effect of the brand image on purchase and word-of-mouth intentions, and provides practical implications for the same.

• Journal of Distribution Science
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• v.18 no.9
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• pp.77-86
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• 2020

Purpose: This study focused on SNS, which has been in the spotlight as a marketing tool as the number of people using SNS, to find out about the relationship between the characteristics of airline SNS marketing and the impact on brand attitude and purchasing intention. It will also identify the relationship between each factor and, in conclusion, identify the influence of SNS characteristics as marketing tools of airlines and provide direction and theoretical implications so that they can be used as effective marketing tools based on this. Research design, data: Airline SNS characteristics factors were derived from three main components: interactivity, entertainment, and convenience, four hypotheses were set up, and the SPSS Win 18.0 program and AMOS 22.0 were used to analyze the relationship between factors in a total of 333 questionnaires. Results: The airline's successful SNS marketing directly affects the airline's brand image and airline's brand attitude, and a good brand image forms a positive brand attitude for consumers and also suggests that this can lead to purchasing intentions. Conclusions: Airlines that want to successfully market SNS should pay attention to SNS characteristics and consider them in-depth, and pay attention to SNS as an important marketing tool.

• Smart Media Journal
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• v.5 no.3
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• pp.54-61
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• 2016

According to many smart devices are development, SNS(Social Network Service) users are getting higher that is possible for real-time communicating, information sharing without limitations in distance and space. Nowadays, SNS users that based on communication and relationships, are getting uses SNS for information sharing. In this paper, we used the SNS posts for users to extract the category and information provider, how to following of recommend method. Particularly, this paper focuses on classifying the words in the text of the posts and measures the frequency using Inception-v3 model, which is one of the machine learning technique -CNN(Convolutional Neural Network) we classified image word. By classifying the category of a word in a text and image, that based on DMOZ to build the information provider DB. Comparing user categories classified in categories and posts from information provider DB. If the category is matched by measuring the degree of similarity to the information providers is classified in the category, we suggest that how to recommend method of the most similar information providers account.

• Smart Media Journal
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• v.11 no.1
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• pp.58-66
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• 2022

As Internet technology develops, SNS users are increasing. As SNS becomes popular, SNS-type crimes using the influence and anonymity of social networks are increasing day by day. In this paper, we propose a fake account classification method that applies machine learning and deep learning to statistical and image data for fake accounts classification. SNS account data used for training was collected by itself, and the collected data is based on statistical data and image data. In the case of statistical data, machine learning and multi-layer perceptron were employed to train. Furthermore in the case of image data, a convolutional neural network (CNN) was utilized. Accordingly, it was confirmed that the overall performance of account classification was significantly meaningful.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.3
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• pp.427-439
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• 2019

This study investigated the semantic network based on the focus of the fashion image and SNS text utilized by global SPA brands on the last seven years in terms of the quantity and quality of data generated by the fast-changing fashion trends and fashion content-based media environment. The research method relocated frequency, density and repetitive key words as well as visualized algorithms using the UCINET 6.347 program and the overall classification of the text related to fashion images on social networks used by global SPA brands. The conclusions of the study are as follows. A common aspect of global SPA brands is that by looking at the basis of text extraction on SNS, exposure through image of products is considered important for sales. The following is a discriminatory aspect of global SPA brands. First, ZARA consistently exposes marketing using a variety of professions and nationalities to SNS. Second, UNIQLO's correlation exposes its collaboration promotion to SNS while steadily exposing basic items. Third, in the case of H&M, some discriminatory results were found with other brands in connectivity with each cluster category that showed remarkably independent results.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.119-128
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• 2019

This study examines the effect of Korean Wave recognition on the preference of cheese chicken ribs in Vietnamese students. It also examines the effect of preference of cheese chicken ribs on the Korean food image of Vietnamese students and their intention to visit Korean restaurants. We analyze the results and try to help globalization of Korean food, development of Korean menu and marketing activities. As a result of the analysis, the hypothesis that the recognition of Korean Wave has positive (+) influence on the preference of cheese chicken ribs was not adopted. The recognition of Hallyu influenced the preference of cheese chicken ribs through SNS influence. SNS influence was found to be a mediator between Korean recognition and cheese chicken rib preference. In case of foreigners, they will recognize Korean Wave through various instruments. Based on the results of this study, it is necessary to study various factors that affect the preference of Korean food and the preference of single menu, and to re - examine Korean food which can globalize Korean food.

• Journal of Information Technology Services
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• v.13 no.4
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• pp.377-396
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• 2014

There is a phenomenon that the consumers from all over the countries are using the Korean online shopping malls, which has settled as a distribution industry. To get the attention of the consumers from other countries, the marketing strategy is important in order for the online shopping malls to go advance abroad. The purpose of this study is to overview the Pinterest, which is a shopping-oriented Social Network Service (SNS) based on the image content. The Pinterest is a valuable online shopping mall marketing channel. By looking at the background growth and feature of service, the existence of the mega SNS as a center in the social business is to see how Pinterest is targeting a niche market. As a result of this study, Pinterest has the advantage against other SNS for joining with online shopping malls because a tendency of the traffic referrals from Pinterest is increasing and the average of the cost of the purchase is high. Therefore, this study is reflecting various cases of utilizing the online shopping malls. In conclusion, Pinterest represents an illustrative case of effective marketing channel of the online shopping malls.

• 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 the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.143-150
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• 2022

Audio-based SNS also needs a visual guide to reach the contents desired by the users. Therefore, this study investigates visual interface design elements that influence the experience of using audio contents in audio-based SNS. Prior researches have identified that the generally acknowledged interface design elements are important for the usability of audio contents. Through the analysis of the currently launched audio-based SNS, the influence of general interface elements were again confirmed, and via the analysis of other audio content services, a new interface evaluation element was explored. Accordingly, with five general interface evaluation elements-layout, color, icon, typography, graphic image, multimedia elements are newly defined and proposed as crucial factors in evaluating the UI of audio-based SNS.