• Fashion & Textile Research Journal
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• v.18 no.4
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• pp.477-488
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• 2016

This study classified and analyzed the types of images posted on official accounts operated by domestic and foreign SPA brands on Instagram and Pinterest, which are image-based fashion curations, and performed a survey on preferred image types in the fashion curations of SPA brands. It aims to induce active apparel purchasing behavior of consumers through the suggestion of image types about fashion curations for effective communication between fashion brands and consumers. The survey to targets the 20s and 30s was carried out from October 23, 2015 until November 22 and conducted factor analysis, paired t-test. The above images were classified into four types based on previous studies: product images, brand images, lifestyle images, multiple images. The results of the survey were also divided into four factors in line with the classification of image types. Generally, foreign SPA brands(H&M, Uniqlo, Zara) used image-based fashion curation services more frequently than domestic SPA brands(8Seconds, Mixxo, Spao, Tngt). The analysis of image types in the fashion curations of SPA brands showed that product images accounted for the highest proportion of images used in the official accounts of SPA brands. However, the comparison of averages on the preferred image types of survey respondents showed that the users who had once visited the official accounts of SPA brands on Instagram and Pinterest preferred in the order of lifestyle information > product information > brand information > multiple information provided by SPA brands, which was statistically significant.

• 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 Korea Society of Computer and Information
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• v.25 no.10
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• pp.255-260
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• 2020

In this paper, I propose an efficient brand identity strategy by topic modeling the Instagram posts, one of SNS(Social Network Service) having more than 1billion world-wide and 500 million daily users. Since the 92% age groups of the Instagram is 18~50 years old (59% 18~29y and 33% 30~49), I set research analysis target three mobile commerce sites to dress and cosmetics sales sites that sale apparels cosmetics and gadgets that recently opened and have operated marketing on diverse channel including SNS. By topic modeling SNS posts for 6 months after launching the site that tagged each m-commerce site brand name or company name, I validate companies' brand identity strategy works effectively and suggest moderation of strategy for brand image. As a result, I found one of three mobile commerce site has different brand image by users and need different identity set up.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.323-333
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• 2021

Lil Miquela, who appeared on social media in 2016, is one of the most popular virtual influencers. In particular, Miquela is having a great impact on society by continuing to collaborate with many fashion brands through Instagram. As the activity of virtual influencers is emerging today, this study aims to derive the meanings of contemporary fashion through analyzing Miquela's social media case. This study analyzed Miquela's Instagram posts as research subjects. As a result of the above analysis, it was possible to classify the methods and devices for expressing fashion in Miquela's social media into three categories: storytelling, reality, and tags & hyperlinks. In addition, the meanings of fashion could be derived from three aspects: the object of experience, the direction of technology, and the realization of the spirit of the times. After appearing on social media, Miquela, who has gradually expanded her domain, is a virtual fashion influencer who has built her identity through fashion, and is expected to give new meaning to fashion in the future.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1125-1133
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• 2014

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

• The Research Journal of the Costume Culture
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• v.23 no.3
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• pp.498-511
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• 2015

This paper examines advertising images of fashion brands in vertical social network site (SNS) from the viewpoints of message strategies. Vertical social network sites are types of social curation systems applied to social networking, where information is selected, organized, and maintained. Fashion brands communicate with consumers by presenting images on vertical SNSs, anticipating improvements in brand image, popularity, and loyalty. Those images portray content for particular brands and seasonal concepts, thus creating paths for product sales information. Marketing via SNSs corresponds to relationship marketing, which refers to long-term interrelationship and value augmentation between the company and consumer, and viral advertising, which relies on word of mouth distribution via social network platforms. Taylor's six-segment message strategy wheel, often used for analyzing viral ads, was applied to conduct a content analysis of the images. A total of 2,656 images of fashion brands advertised on Instagram were selected and analyzed. Results indicated that brand values were somewhat related to the number of followers. Follower rankings and comment rankings were also correlated. In general, fashion brands projected sensory messages most often. Acute need and rational messages were less common than other messages. Sports brands and luxury brands presented sensory messages, whereas fast fashion brands projected routine images most often. Fashion brands promoted on vertical SNSs should portray advertising images that combine message strategies

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.173-180
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• 2021

Recently, the importance of competitive cities has emerged, and many cities around the world are striving to gain competitiveness. Domestic cities are also enhancing their competitiveness by taking advantage of the city's uniqueness and locality with strategies differentiated from other cities, and interest in city brands is increasing. This study seeks to enhance the city brand by improving the landscape elements of the airport, a representative international entrance. Through Instagram's hashtag function, it aims to derive elements of landscape preferred by airport users and to find ways to enhance Busan's city brand based on them.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.888-889
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• 2023

문서를 통해 기록을 남기는 과거의 기록 방식은 현대에 이르러 블로그, 인스타그램 등 다양한 SNS를 활용하는 방식으로 변모하고 있다. SNS의 발달과 대중화는 현대인에게 일반적인 일기 작성 포맷으로 자리 잡고 있다. 증가하는 수요와 디지털 기술 혁신에 대비되는 기존의 수동적인 일기 작성 애플리케이션을 대체하기 위해 본 논문은 DALL-E2와 블록체인을 활용한 일기 작성 및 민팅 애플리케이션 구현을 제안한다. 사용자는 제안하는 애플리케이션을 통해 음성인식, 광학 문자인식을 통한 다양한 일기 작성 방식을 제공받고, 완성된 일기 이미지를 디지털 자산으로서 보존할 수 있다.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.851-859
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• 2017

Today, with the advent and development of Social Network Service (SNS), various types of information that have been difficult to observe have been pouring out. Recently, Vertical Social Networking Service (SNS), a service that shares specific interests with users' Vertical Social Networking Service) is emerging as a major research area. Especially, various human, social and spatial characteristics can be observed through geolocation data and social data collected through mobile GPS, and it is used in various studies. In this study, we analyze the social data collected through the image - based vertical SNS Instagram, and measure the user 's experience based on the social media based on the user' s spatial context. Therefore, in this study, we investigate what types of spatial patterns exist between experiential elements of sharing experiences and geographical characteristics through social data, and examine a new model of shared experience structure through extracted data.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.