• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.93-98
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• 2023

Instagram is one of the fastest-growing online photo social web services where users share their life images and videos with other users. Image tagging is an essential step for developing Automatic Image Annotation (AIA) methods that are based on the learning by example paradigm. Hashtags can be used on just about any social media platform, but they're most popular on Twitter and Instagram. Using hashtags is essentially a way to group together conversations or content around a certain topic, making it easy for people to find content that interests them. Practically on average, 20% of the Instagram hashtags are related to the actual visual content of the image they accompany, i.e., they are descriptive hashtags, while there are many irrelevant hashtags, i.e., stophashtags, that are used across totally different images just for gathering clicks and for search ability enhancement. Hence in this work, Sorting instagram hashtags all the way through mass tagging using HITS (Hyperlink-Induced Topic Search) algorithm is presented. The hashtags can sorted to several groups according to Jensen-Shannon divergence between any two hashtags. This approach provides an effective and consistent way for finding pairs of Instagram images and hashtags, which lead to representative and noise-free training sets for content-based image retrieval. The HITS algorithm is first used to rank the annotators in terms of their effectiveness in the crowd tagging task and then to identify the right hashtags per image.

• Asia pacific journal of information systems
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• 제33권3호
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• pp.768-791
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• 2023

Effective brand management using images has been a challenge for the brand managers. The brand identity-brand image alignment on the social media is an important yet mostly-overlooked phenomenon. We proposed a scalable Google Cloud Vision-based approach for measuring the alignment between brand identity and brand image, and understanding the brand positions. We analyzed 3247 images of 13 leading Indian brands on Instagram. Images containing wordy announcements by the firms are in stark contrast with the relatively more emotive images by the users. It leads to a noticeable disconnect between the brand identity and brand image. Also, the private sector brands do not always outperform the public sector brands in branding efforts. By offering practical guidance on how to measure and reduce the misalignment, this study paved a feasible path towards better visual branding on Instagram.

• 한국멀티미디어학회논문지
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• 제23권8호
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• pp.1049-1058
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• 2020

'Instagrammable' is a new term which means a photo or a series of pictures are worth posting on Instagram. Since Instagram is an image-oriented social media platform, it is important to give users proper awareness through images in order to be an instagrammable post. In this study, we explored the proper delivery method of messages within instagrammable posts through the use of hashtags(#). Specifically, we paid attention to the use of 'Card News', which involves a series of images that form a short narrative. Hashtags play an important role that they often describe sharing intention of the post, and we found analyzing the use of hashtags in Card News posts is a good indicator of users' Instagram activities. Currently, there are more than 580k posts are found with the search keyword Card News, and the number is increasing. In this study, we collected and analyzed more than 50k hashtags on Instagram to explore how news stories are posted from both the general users and news media accounts. Furthermore, we conducted interviews with journalists to analyze how news media are making use of Instagram as a legitimate place to share news stories with impact.

• 한국의상디자인학회지
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• 제20권3호
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• pp.49-62
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• 2018

The purpose of this study is to examine women's street fashion based on Instagram by word cloud analysis. This study is divided into items, silhouettes, colors, materials, patterns, and images that appear in women's street fashion. The results of this study are as follows: First, women's fashion-oriented Instagram accounts have a maximum of 8.6 million followers, with 16 blogs have more than one million users. As for the fashion-oriented Instagram visitors, many were their 10s-20s and photography was the key issue. Second, it was found that the casual image, which is the basis of street fashion, romantic, elegance, active sportive image, and sexy images appeared as unique images, and mixed with each other. Third, we compared the fashion characteristics of the top blogs 'fashionnova', 'fashionclimaxx2', and 'fashion.selection'. The blog 'fashionnova', utilizes sexy images and various dresses, and dresses were the characteristic points. The blog 'fashionclimaxx2' features casual images and modern office looks. The blog 'fashoin.selection' has fashion characteristics of both 'fashionnova' and 'fashionclimaxx2'.

• 복식문화연구
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• 제29권4호
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• pp.603-615
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• 2021

The aim of this study was to analyze the semantic network structure of keywords and the visual composition of images extracted from Instagram in relation to the multi-persona phenomenon with in fashion imagery, which has recently been attracting attention. To this end, the concept of a 'secondary character', which forms a separate identity from a 'main character' on various social media platforms as well as on the airwaves, was considered as the spread of multi-persona and #SecondaryCharacter on Instagram was investigated. 3,801 keywords were collected after crawling the data using Python and morphological analysis was undertaken using KoNLP. The semantic network structure was then examined by conducting a CONCOR analysis using UCINET and Netdraw to determine the top 50 keywords. The results were then classified into a total of 6 clusters. In accordance with the meaning and context of the keywords included in each cluster, group names were assigned : virtual characters, relationship with the main character, hobbies, daily record, N-job person, media and marketing. Image analysis considered the technical, compositional, and social styles of the media based on Gillian Rose's visual analysis method. The results determined that Instagram uses fashion images that virtualize one's face to produce multi-persona representation s that show various occupations, describe different types of hobbies, and depict situations pertaining to various social roles.

• 인터넷정보학회논문지
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• 제18권5호
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• pp.61-67
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• 2017

본 논문에서는 딥러닝의 회선신경망을 이용한 실제 소셜 네트워크 상의 이미지 분류가 얼마나 효과적인지 알아보기 위한 실험을 수행하고, 그 결과와 그를 통해 알게 된 교훈에 대해 소개한다. 이를 위해 ImageNet Large Scale Visual Recognition Challenge(ILSVRC)의 2012년 대회와 2015년 대회에서 각각 우승을 차지한 AlexNet 모델과 ResNet 모델을 이용하였다. 평가를 위한 테스트 셋으로 인스타그램에서 수집한 이미지를 사용하였으며, 12개의 카테고리, 총 240개의 이미지로 구성되어 있다. 또한, Inception V3모델을 이용하여 fine-tuning을 실시하고, 그 결과를 비교하였다. AlexNet과 ResNet, Inception V3, fine-tuned Inception V3 이 네 가지 모델에 대한 Top-1 error rate들은 각각 49.58%, 40.42%, 30.42% 그리고 5.00%로 나타났으며, Top-5 error rate들은 각각 35.42%, 25.00%, 20.83% 그리고 0.00%로 나타났다.

• 한국멀티미디어학회논문지
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• 제17권9호
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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.

• 한국의류학회지
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• 제42권3호
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• pp.379-396
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• 2018

This study investigated consumer perceptions of information provided in a fashion Instagram. This study examined the differences between information provided in Instagram by brand vs consumers. A pilot test was conducted to develop stimuli and a brand selection in the main study. Participants were randomly assigned to one of two stimuli manipulated by information providers, and examined the perceived credibility, usefulness, and enjoyment of information as well as brand attachment and purchase intention. We gathered and analyzed a total of 200 data. The findings of the study showed that respondents perceived significantly greater usefulness and purchase intention of images uploaded by consumers compared to the fashion brand. Credibility and enjoyment were significant factors to enhance brand attachment; in addition, usefulness, credibility, and enjoyment were significant factors to increase purchase intention. The findings of the study suggest academic and marketing implications.

• 복식문화연구
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• 제31권4호
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• pp.467-488
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• 2023

The purpose of this study is to determine the concepts of heterotopic image and fashion space, and the characteristics of fashion space and images from the perspective of fashion brands and users. This study examines the evolution of fashion space and consumers with it, based on Foucault's theory of heterotopia, which refers to spaces that blend contradictory features not typically found within a single physical structure. This is accomplished by employing a single case study of Ader Error's Ader Space, a Seoul-based brand known for its unique approach to presenting and communicating fashion. Based on an analysis of Instagram posts of Ader Error along with the hashtag searches "aderspace" and "adererror", this study categorizes heterotopia from the perspective of fashion brands into three properties: fashion space as a medium for selling fashion products; fashion space as getaway to hybrid fashion practices; and fashion space as an illusionary place to experience fashion. From the user perspective, the heterotopic image of Ader Space portrayed on Instagram is characterized by the image of fashion products in an extraordinary fashion space, the image of a fashion space beyond space and time, and the image of exposing the hidden and the illusion-compensation of fashion space. This study contributes to a heightened understanding of the evolutionary concept of the fashion space.

• 한국정보시스템학회지:정보시스템연구
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• 제28권4호
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• pp.199-221
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• 2019

Purpose The research investigated on what motivates the consumers to use the SNS, what qualities of images are preferred and how the pleasure and arousal derived from looking at the images have moderating effects on sharing images, following accounts, clicking profile links of accounts and accessing the link on profiles to purchase products. Design A survey was conducted by using actual images published on the Instagram profiles of an online shopping mall. Findings As a result, their emotional responses such as pleasure or arousal on the four of behavioral intentions changed the impact of SNS use motivation on the behavioral intentions. When one felt pleasure, the behavioral intentions of sharing activities and clicking links is further triggered.