• 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.

• Journal of KIISE
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• v.43 no.1
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• pp.47-53
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• 2016

While the Internet develops rapidly, a huge amount of image data collected from smart phones, digital cameras and black boxes are being shared through social media sites. Generally, social images are handled by tagging them with information. Due to the ease of sharing multimedia and the explosive increase in the amount of tag information, it may be considered too much hassle by some users to put the tags on images. Image retrieval is likely to be less accurate when tags are absent or mislabeled. In this paper, we suggest a method of extracting tags from social images by using image content. In this method, CNN(Convolutional Neural Network) is trained using ImageNet images with labels in the training set, and it extracts labels from instagram images. We use the extracted labels for automatic image tagging. The experimental results show that the accuracy is higher than that of instagram retrievals.

• 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

• Journal of the Korean Society of Costume
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• v.67 no.3
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• pp.115-132
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• 2017

This study recognizes the importance of the social network platform as a new fashion media, and analyzes the significance of various digital fashion images, based on the 'Aura' theory of Walter Benjamin. The concept of "Disappearance of Artistic Aura" can be summarized into three discussions: 1) the change in the way of artistic perception, which is changes in value from worship to exhibition. 2) the change in the way of artistic acceptance, from personal to mass. 3) the emergence of new artistic concepts such as camera and film. By reviewing characteristics of the $21^{st}$ digital replication era, the study tried to discover and evaluate the expanded significance of the 'Aura' represented on digital fashion images, which are infinitely generated, modified, reproduced, transmitted, and shared in social network environments. The 'Burberry Instagram' was chosen as the subject of the study. The study reviewed around 2,500 images, which were uploaded from February 2011 to July 2016, and selected 200 images deemed the most representative of Burberry, and categorized and analyzed by the extended concept of 'Aura'. The study results as follows: First, the 'Aura' in digital fashion image appearing on social network platforms signifies the expansion of product value in fashion, and it also represents inherited traditions and modernization of images. Second, it also signifies the democratization and globalization of fashion through the open replication and sharing as well as the interaction of criticism and acceptance. Third, it signifies the personalized taste and fashion as everyday lifestyle, through personalized services, securing playful space, and real-time updates.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.401-428
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• 2021

Recently, libraries are trying to communicate with users using various social media. Among them, Instagram is the most used SNS by users recently. Therefore, in this study, in order to effectively operate the library Instagram, we looked at how Instagram in the library is operated, what posts and contents people are interested in, and how the library can utilize it. By analyzing the Instagram operation status of Instagram, we tried to suggest improvement plans and activation plans. For this purpose, theoretical background research on SNS and Instagram, analysis of prior research, and related data were collected and analyzed. Next, for 82 domestic library accounts opened on Instagram, the library type, region, and Instagram account number of posts, 'followers', 'follows', images, etc. were collected, and the Text, hashtags, upload date, number of 'likes' and comments were analyzed. As a result of the study, it was found that increasing followers, uploading user-customized posts, formalizing account profiles, using library-specific hashtags, and communication with users are necessary to activate library Instagram.

• Journal of Information Science Theory and Practice
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• v.6 no.2
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• pp.46-61
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• 2018

The mobile social networking application Instagram is a well-known platform for sharing photos and videos. Since it is folksonomy-oriented, it provides the possibility for image indexing and knowledge representation through the assignment of hashtags to posted content. The purpose of this study is to analyze how Instagram users tag their pictures regarding different kinds of picture and hashtag categories. For such a content analysis, a distinction is made between Food, Pets, Selfies, Friends, Activity, Art, Fashion, Quotes (captioned photos), Landscape, and Architecture image categories as well as Content-relatedness (ofness, aboutness, and iconology), Emotiveness, Isness, Performativeness, Fakeness, "Insta"-Tags, and Sentences as hashtag categories. Altogether, 14,649 hashtags of 1,000 Instagram images were intellectually analyzed (100 pictures for each image category). Research questions are stated as follows: RQ1: Are there any differences in relative frequencies of hashtags in the picture categories? On average the number of hashtags per picture is 15. Lowest average values received the categories Selfie (average 10.9 tags per picture) and Friends (average 11.7 tags per picture); for highest, the categories Pet (average 18.6 tags), Fashion (average 17.6 tags), and Landscape (average 16.8 tags). RQ2: Given a picture category, what is the distribution of hashtag categories; and given a hashtag category, what is the distribution of picture categories? 60.20% of all hashtags were classified into the category Content-relatedness. Categories Emotiveness (about 4.38%) and Sentences (0.99%) were less often frequent. RQ3: Is there any association between image categories and hashtag categories? A statistically significant association between hashtag categories and image categories on Instagram exists, as a chi-square test of independence shows. This study enables a first broad overview on the tagging behavior of Instagram users and is not limited to a specific hashtag or picture motive, like previous studies.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.123-131
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• 2019

Social network service users actively express and share their feelings about social issues and content of interest through postings. As a result, the sharing of emotions among individuals and community members in social network is spreading rapidly. Therefore, resulting in active research of emotion analysis on posting of users. However, There is insufficient research on emotion analysis for postings containing various emotions. In this paper, we propose a method that analyzes the emotions of an Instagram posts using hashtags and images. This method extracts representative emotion from user posts containing multiple emotions with 66.4% accuracy and 81.7% recall, which improves the emotion classification performance compared to the previous method.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.81-89
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• 2022

This study aims to analyze the images of Instagram posts and to draw implcations regarding the exhibition of . This study collects and crawl 24,295 images from Instagram posts as a dataset. We use the Google Cloud Vision API for labeling the images and a total of 212,567 clusters of labels are finally classified into 9 categories using Word2Vec. The categories of museum spaces, photo zone, architecture category are dominant along with people category. In conclusion, visitors curate their experiences and memories of physical places and spaces while they are experiencing with the exhibition. This result reproves the results of previous studies which emphasize a sense of social presence and place making. The convergent approach of art management and art technology used in this study help museum professionals have an insight on big data based visitor research on a practical level.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.64-77
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• 2022

The advent of location-based social networks (LBSNs), and the pervasive use of smartphones have allowed individuals to easily inform their status through locational information. This led to a new trend in social media: to upload geotagged photos that illustrate the location of the images and then share them with others. In this circumstance, the current study aims to examine the use of geotags on Instagram. Further, the motivations for using geotags as well as the relationship among the motivation, satisfaction, and location information sharing behavior are analyzed. The online survey was conducted on 411 respondents of Hong Kong who are active Instagram users. Based on uses and gratification theory and goal theory, the users' motivations and goals for utilizing geotags were divided into mainly two categories; task-involved and self-involved goals. Then, four different motivations (contribution, memory aid, showing off, and reputation gaining) were further examined. The result indicated that contribution, memory aid, and reputation gaining were the goals and motivation for the users to utilize geotags on Instagram, having a positive impact on satisfaction. However, a positive relationship between showing off and geotag satisfaction was not supported. Among four different factors, memory aid was found to have the strongest influence on geotagging satisfaction. The result of testing the relationship between geotag satisfaction and further location information sharing behavior also turned out to have a positive relationship. The implications and limitations of findings are also discussed in the study.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.1-25
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• 2023

This study aims to propose implications for the development of archival content of archives management institutions in Korea by analyzing cases of the archival content on Instagram of the national archives in the Anglosphere. The basic information of the research target's Instagram account, including the creation date, content, and the number of followers, was investigated, and the posts' contents and interaction types with high user responses were analyzed. As a result, to spread the records information service using Instagram, producing images and short-form content that can be intuitively checked through mobile screens and creating content that will attract the attention of primary users are required. Moreover, it is necessary to develop content for informative communications that can be shared with other users. There is also a need to enhance the exposure and searchability of the institution's Instagram account by strengthening connections with the institution's existing online resources and enabling communications, such as using hashtags, following related institutional accounts, and providing feedback on the contents' comments with followers. This study is meaningful in that it examined cases of archival content for Instagram and suggested their applications, and it can be used as basic data to help plan archival contents to spread the archival culture.