본 연구는 Google Play에서 수집된 Instagram 사용자 리뷰에 대한 심층 분석을 통해, 이 연구는 애플리케이션의 성능과 사용자 만족도에 대한 중요한 통찰력을 얻고자 한다. 텍스트 마이닝과 감성 분석 기술을 활용하여 사용자 리뷰에 담긴 감성과 의견을 체계적으로 파악하며, 이를 통해 앱의 개선점과 사용자 경험을 깊이 이해하려고 한다. 인스타그램 리뷰가 사용자들의 다양한 경험을 어떻게 반영하는지, 그리고 앱의 장단점을 어떻게 드러내는지를 분석 한다. 이를 위해 나이브 베이즈 알고리즘을 사용한 감성 분석을 수행하며, 이 결과는 인스타그램 서비스 개선에 도움 이 될 것으로 기대된다. 연구는 또한 개발자들이 사용자 피드백을 더 잘 이해하고 활용하는 데 도움을 주며, 결국 사용자 만족도를 향상시키는 데 기여할 것으로 예상된다. 이 연구는 소셜 미디어 사용 패턴과 사용자 의견의 복잡한 관계를 탐색하고, 이를 통해 더 나은 사용자 경험을 제공하는 방안을 모색한다.

최근 소셜미디어 이용이 심리적 웰빙에 미치는 영향이 부각되고 있으나 어떤 요소가 소셜미디어 상에서의 관계 의 질을 예측할 수 있는지에 대한 연구는 상대적으로 드물다. 본 연구는 머신러닝 기법을 이용하여 COVID-19로 인한 자가격리 동안 인스타그램 활동과 외로움, 우울 등의 심리 상태가 소셜미디어 상에서의 관계의 질을 예측할 수 있는지 알아보고자 하였다. 성인 95명을 대상으로 자가격리 중과 자가격리 해제 후 시점에서 외로움, 인스타그 램 활동, 소셜미디어 상에서의 관계, 우울 등에 대해 자기보고식 설문에 응답하도록 하였다. 그 후, 다차원 척도법과 표상유사성분석, 분류분석을 각 시점에 대해 수행하였다. 다차원척도법 결과, 1차원에서 인스타그램 이용 시간과 우울이 다른 변인들과 구별되었으며, 2차원에서 외로움과 수동적 이용이 다른 변인들과 구별되었다. 그 후 소셜미 디어 상에서의 관계의 질의 고,저 집단에 대해 표상유사성분석을 실시한 결과, 소셜미디어 상에서의 관계의 질이 높은 집단은 낮은 집단보다 자가격리의 영향을 더 많이 받는 것으로 나타났다. 분류분석 결과에서도 소셜미디어 상에서의 관계의 질 예측 변인이 사회적 고립의 여부에 따라 달라지는 것으로 나타났다. 따라서 본 연구의 결과는 사람들이 사회적 고립 상황에 있지 않을 때 인스타그램 이용 변인과 심리적 변인이 소셜미디어 상에서의 관계를 더 잘 예측할 수 있음을 시사한다.

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 illusioncompensation of fashion space. This study contributes to a heightened understanding of the evolutionary concept of the fashion space.

In order to communicate brand concepts and values to the young generations, many brands are highly active on social media platforms such as Twitter, Facebook, and Instagram. Brand-Generated Content has already become the most common marketing strategy for fashion brands and plays a significant role in influencing consumers’ purchase intention. With increased competition on social media platforms, companies need to understand which posting features can bring in more consumer engagements such as number of likes and comments on social media platforms. In this paper, we develop (1) a model to predict the number of likes and (2) a methodology to detect anomaly of posts that have unusually high percentage of negative user comments based on Instagram design variables, including semantic text meanings, facial expressions, color scheme and background of photos, and post timing, among others. We collected a data set of brand-generated Instagram posts from ten fashion brands. The data covers the image, text, and user comments posted between 2019 and 2020. Image features were extracted using Convolutional Neural Network, and text topics were generated through Latent Dirichlet Allocation. Our results will help managers design Instagram posts to increase consumer engagement and to reduce negative consumer reactions.

Consumer brand engagement (CBE) signals propensity for brand purchase. A scale proposes three dimensions of CBE (i.e., cognitive, affective and activation dimensions) but the dimensions prominent and driving brand purchase intentions in an Instagram cosmetic purchase context need examination. In this context, this study tests Hollebeek, Glynn and Brodie’s (2014) 10-items/3 dimensions scale and examines an outcome of cosmetics brand purchase intention on Instagram. Data was quantitatively collected from 203 consumers who were students and non-students using convenience and snowballing non- probability sampling method. Confirmatory factor analysis and structural equation modelling were used to analyse the data. The results revealed that although the three CBE dimensions were identified in a Cosmetic Instagram purchase context, it was the affective and activation dimensions that positively predicted consumers’ intentions to purchase cosmetic brands after engaging with the brand on Instagram. Theoretical and practical implications are provided.

Social media began to boom in the 2000s. According to statistics, there are 92.3% of internet users are social media users who spend nearly two and a half hours daily on social media. Instagram is considered the most popular image-sharing platform, with more than 1.2 billion monthly active users. Meanwhile, consumers nowadays refer to and follow online reviews to assist their decision-making process more efficiently.

Social media have emerged as one of the most important tools for firms to engage customers (e.g., Chandrasekaran et al., 2022; Cheng & Edwards, 2015; Lee et al., 2018; Wedel & Kannan, 2016). Within the tourism industry, scholars have investigated the role of social media communication in various contexts, such as online travel information search (Xiang & Gretzel, 2010), sharing travel experiences (So et al., 2018; Wang et al., 2022) and establishing positive customer relationships (Jamshidi et al., 2021). Insights into which social media content makes for generating positive engagement are, however, still largely based on marketers’ intuitions or focusing on message factors of social media posts such as message appeals (e.g., Wang & Lehto, 2020). It also often neglects the importance of the visual component of social media posts, and only a few research have investigated the effects of the image in social media on the travel industry (e.g., Fusté-Forné, 2022). The objective of this research is, therefore, to understand how textual features and image features generate user engagement in social media utilizing cutting-edge transfer learning techniques and to propose how these features should be customized to maximize user engagement for online travel shopping companies. We collect and analyze more than 10,000 Instagram posts from three online travel shopping companies, including Expedia, Priceline, and Kayak. The results from transfer learning algorithms utilizing 24 features, such as the number of people in the image, emotions expressed in the people in the image, hue, and RGB value, successfully predict the level of engagement measured by the number of likes and comments.

Instagram marketing is a popular tool for communication in the tourism industry. However, research into effective execution tactics has been limited to the content, recipient characteristics, and sender types (e.g., celebrities) (i.e., Ferwerda & Tkalcic, 2018; Jin et al., 2019; Singh, 2020). The layouts of Instagram ads themselves have received little scholarly attention. Instagram ads typically convey multiple pieces of information in a single advertisement unit, raising concerns about the significance of the order in which the information is presented. Specifically, we must understand how different orders of presenting information affect a firm’s performance. Therefore, this study investigates the effect of presentation order on consumer behavioral intentions toward tour programs promoted on Instagram.

This study examines how brand-influencer, influencer-users, and user-brand congruences affect perceived fantasy about the influencer and closeness toward the brand when an Instagram ad is endorsed by celebrity (vs. non-celebrity) influencers. The study employed a between-subject online experiment by manipulating an advertisement endorsed by a celebrity and a non-celebrity influencer. The results suggest that congruence between brand-influencer matters in building effective relationships.

The purpose of this study was to identify beauty influencer attributes on Instagram and their impact on product attitude and purchase intention and on influential difference between micro and mega influencers. The survey was conducted using a consumer survey method with a questionnaire, and the subjects of the survey were 506 women in their 20s and 30s using Instagram. The results of the study are as follows: First, a range of influencer attribute sub-factors were derived in relation to expertise, attractiveness, similarity, reliability, and intimacy. Second, the attributes highly impacted product attitude in the increasing order of attractiveness, similarity, reliability, and familiarity, with expertise having no statistically significant influence. Third, the consumer’s attitude toward the product introduced by the beauty influencer had a significant impact on their purchase intention. Fourth, it was shown that there is no difference in attributes according to the influencer’s number of followers. Fifth, the number of followers of the beauty influencer had a partial impact on attitude and purchase intention. A limitation of this study is that age and gender samples are narrow, but it is nevertheless meaningful to explore this topic in the absence of research on beauty influencers. It is believed that these findings will serve as a foundation for the development of beauty influencer marketing strategies on Instagram.

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 multipersona 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.

This study examined the effect of Instagram usage time (short, long) and spending on fashion products (light, heavy) on product attitude and purchase intention of products promoted by an influencer. The moderating effect of influencer type (mega, macro, micro) was also investigated. A total of 515 males and females in their 20s participated in an online survey. Descriptive statistics were analyzed and exploratory factor analysis and two-way ANOVA were conducted. Research findings were as follows. First, the usage time, both short and long, had a positive effect on product attitude. Also, the interactive effects of usage time and influencer type on product attitude were found. Consumers with short Instagram usage time displayed the highest attitude toward products promoted by a macro-influencer whereas consumers with long Instagram usage time displayed the highest attitude toward products promoted by a micro-influencer. Second, usage time and influencer type did not show interactive effects on purchase intention. Third, both categoriacl variables of users’ spending on fashion products had a positive effect on product attitude. Fourth, the interaction effects of spending on fashion products and influencer types on purchase intention were found. The group of light buyers showed the highest purchase intention on products promoted by the macro-influencer while the group of heavy buyers showed the highest purchase intention of products promoted by the micro-influencer. Based on the results, implications were suggested.