• Title/Summary/Keyword: Social Media Text

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An exploratory study on fashion criticism in social media using text mining - Focusing on panel discussion of fashion show in YouTube - (텍스트 마이닝을 이용한 소셜 미디어의 패션 비평에 관한 탐색적 연구 - 유튜브의 패션쇼 Panel discussion을 중심으로 -)

  • Dawool Jung;Se Jin Kim
    • The Research Journal of the Costume Culture
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    • v.32 no.2
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    • pp.215-231
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    • 2024
  • The changing media landscape has diversified how and what is discussed about fashion. This study aims to examine expert discussions about fashion shows on social media from the perspective of fashion criticism. To achieve this goal objectively, a text mining program, Leximancer, was used. In total, 58 videos were collected from the panel discussion section of Showstudio from S/S 21 to S/S 24, and the results of text mining on 24,080 collected texts after refinement are detailed here. First, the researchers examined the frequency of keywords by season. This revealed that in 2021-2022, digital transformation, diversity, and fashion films are now commonly used to promote fashion collections, often replacing traditional catwalk shows. From 2023, sustainability and virtuality appeared more frequently, and fashion brands focused on storytelling to communicate seasonal concepts. In S/S 2024, the rise of luxury brand keywords and an increased focus on consumption has been evident. This suggests that it is influenced by social and cultural phenomena. Second, the overall keywords were analyzed and categorized into five concepts: formal descriptions and explanations of the collection's outfits, sociocultural evaluations of fashion shows and designers, assessments of the commerciality and sustainability of the current fashion industry, interpretations of fashion presentations, and discussions of the role of fashion shows in the future. The significance of this study lies in its identification of the specificity of contemporary fashion criticism and its objective approach to critical research.

Understanding Brand Image from Consumer-generated Hashtags

  • Park, Keeyeon Ki-cheon;Kim, Hye-jin
    • Asia Marketing Journal
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    • v.22 no.3
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    • pp.71-85
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    • 2020
  • Social media has emerged as a major hub of engagement between brands and consumers in recent years, and allows user-generated content to serve as a powerful means of encouraging communication between the sides. However, it is challenging to negotiate user-generated content owing to its lack of structure and the enormous amount generated. This study focuses on the hashtag, a metadata tag that reflects customers' brand perception through social media platforms. Online users share their knowledge and impressions using a wide variety of hashtags. We examine hashtags that co-occur with particular branded hashtags on the social media platform, Instagram, to derive insights about brand perception. We apply text mining technology and network analysis to identify the perceptions of brand images among consumers on the site, where this helps distinguish among the diverse personalities of the brands. This study contributes to highlighting the value of hashtags in constructing brand personality in the context of online marketing.

A Study on Gamification Consumer Perception Analysis Using Big Data

  • Se-won Jeon;Youn Ju Ahn;Gi-Hwan Ryu
    • International Journal of Advanced Culture Technology
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    • v.11 no.3
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    • pp.332-337
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    • 2023
  • The purpose of the study was to analyze consumers' perceptions of gamification. Based on the analyzed data, we would like to provide data by systematically organizing the concept, game elements, and mechanisms of gamification. Recently, gamification can be easily found around medical care, corporate marketing, and education. This study collected keywords from social media portal sites Naver, Daum, and Google from 2018 to 2023 using TEXTOM, a social media analysis tool. In this study, data were analyzed using text mining, semantic network analysis, and CONCOR analysis methods. Based on the collected data, we looked at the relevance and clusters related to gamification. The clusters were divided into a total of four clusters: 'Awareness of Gamification', 'Gamification Program', 'Future Technology of Gamification', and 'Use of Gamification'. Through social media analysis, we want to investigate and identify consumers' perceptions of gamification use, and check market and consumer perceptions to make up for the shortcomings. Through this, we intend to develop a plan to utilize gamification.

The User Perception in ASMR Marketing Content through Social Media Text-Mining: ASMR Product Review Content vs ASMR How-to Content (텍스트 마이닝을 활용한 ASMR 콘텐츠 분야에 따른 소비자 인식 및 구전효과 차이점 분석: ASMR 제품리뷰 및 ASMR How-to 콘텐츠 중심으로)

  • Tran, Hung Chuong;Choi, Jae Won
    • The Journal of Information Systems
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    • v.30 no.4
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    • pp.1-20
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    • 2021
  • Purpose Nowadays, Autonomous Sensory Meridian Response (ASMR) is rapidly growing in popularity and increasingly appearing in marketing. Not even in TV commercial advertisement, ASMR also fast growing in one-person media communication, many brands and social media influencers used ASMR for their marketing contents. The purpose of this study is to measure consumers' perceptions about the products in ASMR marketing content and compare the differences in communication effect of ASMR content creator between product review and how-to in the same Macro tier influencer - the YouTuber that has 10,000-100,000 subscribers. Design/methodology/approach The research methods selected ASMRtist that do product review content and how-to content, Text comments data was collected from 200 videos of tech-device review videos and beauty-fashion videos. A total of 52,833 text comments were analyzed by applying the LDA topic modeling algorithm and social network analysis. Findings Through the result, we can know that ASMR is good at taking attention of viewers with ASMR triggers. In the Tech device reviews field, ASMR viewers also focus on the product like product's performance and purchase. However, there are many topics related to reaction of ASMR sound, trigger, relaxation. In the Beauty-fashion field, viewers' topics mainly focus on the reaction of the ASMR trigger, response to ASMRtist and other topics are talking about makeup - fashion, product, purchase. From LDA result, many ASMR viewers comment that they feel more comfortable when watching the marketing content that uses ASMR. This result has shown that ASMR marketing contents have a good performance in terms of user watching experience, so applying ASMR can take more consumer intention. And the result of social network analysis showed that product review ASMRtist have a higher communication effectiveness than how-to ASMRtist in the same tier. As an influencer marketing strategy, this study provides information to establish an efficient advertising strategy by using influencers that create ASMR content.

A Study on the User Perception in Fashion Design through Social Media Text-Mining (소셜미디어 텍스트마이닝을 통한 패션디자인 사용자 인식 조사)

  • An, Hyosun;Park, Minjung
    • Journal of the Korean Society of Clothing and Textiles
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    • v.41 no.6
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    • pp.1060-1070
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    • 2017
  • This study seeks methods to analyze users' perception in fashion designs shown in social media using textmining analysis methods. The research methods selected 'men's stripe shirts' as subjects and collected texts related to the subject mainly from blogs. Texts from 13,648 posts from November 1st, 2015 to October 31st, 2016 were analyzed by applying the LDA algorithm and content analysis. As a result, the wearing status per season and subjects of men's stripe shirts were derived. Across the entire period, the main topics discussed by users to be pattern, customized suits, brands, coordination and purchase information. In terms of seasons, spring time showed the sharing of information on coordinating daily looks or boyfriend looks, and during the winter season the information shared were about shirts suitable for special occasions such as job interviews and stripe shirts that match suits. The study results showed that text-mining analysis is capable of analyzing the context and provide a user-centered index responding to demands newly mentioned by users along with the rapid changes in fashion design trends.

Estimating Media Environments of Fashion Contents through Semantic Network Analysis from Social Network Service of Global SPA Brands (패션콘텐츠 미디어 환경 예측을 위한 해외 SPA 브랜드의 SNS 언어 네트워크 분석)

  • Jun, Yuhsun
    • 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.

Microblogging Sentiment Investor, Return and Volatility in the COVID-19 Era: Indonesian Stock Exchange

  • FARISKA, Putri;NUGRAHA, Nugraha;PUTERA, Ika;ROHANDI, Mochamad Malik Akbar;FARISKA, Putri
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.61-67
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    • 2021
  • The covid-19 pandemic scenario caused the most extensive economic shocks the world has experienced in decades. Maintaining financial performance and economic stability is essential during the pandemic period. In these conditions, where movement is severely restricted, media consumption is considered to be increasing. The social media platform is one of the media online used by the public as a source of information and also expressing their sentiment, including individual investors in the capital market as social media users. Twitter is one of the social media microblogging platforms used by individual investors to share their opinion and get information. This study aims to determine whether microblogging sentiment investors can predict the capital market during pandemics. To analyze microblogging sentiment investors, we classified sentiment using the phyton text mining algorithm and Naïve Bayesian text classification into level positive, negative, and neutral from November 2019 to November 2020. This study was on 68 listed companies on the Indonesia stock exchange. A Vector Autoregression and Impulse Response is applied to capture short and long-term impacts along with a causal relationship. We found that microblogging sentiment investor has a significant impact on stock returns and volatility and vice-versa. Also, the response due to shocks is convergent, and microblogging investors in Indonesia are categorized as a "news-watcher" investor.

The Persuasive Impact of Fit between Message Goals(Promotion vs. Prevention) and Modality of Message on Social Media (메시지 조절목표와 메시지 형식 간 적합성이 메시지 설득력에 미치는 영향)

  • Kim, Dong Hoo;Song, Young-A
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.604-621
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    • 2021
  • Examination of the concurrent evolution of communication tools and eating behaviors over recent decades reveals that social media and other forms of digital content have become powerful new driving forces for nutritional choices and food consumption. The purpose of this research was to examine the effect between goal orientation of message (promotion versus prevention) and the type of message (text versus image) on effectiveness of the message. The findings showed that individuals exposed to a promotion-focused message similarly responded to the message regardless of the type of the message. By contrast, those who exposed to a prevention-focused message showed significantly more positive responses to the message posted on the text-based social media than the message on the image-based social media. The findings indicated that, if presented effectively, social media could be harnessed to promote healthier eating habits and behaviors, prevent those which can be harmful, and ultimately improve an individual's daily food consumption and overall quality of life.

Sell-sumer: The New Typology of Influencers and Sales Strategy in Social Media (셀슈머(Sell-sumer)로 진화한 인플루언서의 새로운 유형과 소셜미디어에서의 세일즈 전략)

  • Shin, Hajin;Kim, Sulim;Hong, Manny;Hwang, Bom Nym;Yang, Hee-Dong
    • Knowledge Management Research
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    • v.22 no.4
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    • pp.217-235
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    • 2021
  • As 49% of the world's population uses social media platforms, communication and content sharing within social media are becoming more active than ever. In this environmental base, the one-person media market grew rapidly and formed public opinion, creating a new trend called sell-sumer. This study defined new types of influencers by product category by analyzing the subject concentration of the commercial/non-commercial keywords of influencers and the impact of the ratio of commercial postings on sales. It is hoped that influencers working within social media will be helpful to new sales strategies that are transformed into sell-sumers. The method of this study classifies influencers' commercial/non-commercial posts using Python, performs text mining using KoNLPy, and calculates similarity between FastText-based words. As a result, it has been confirmed that the higher the keyword theme concentration of the influencer's commercial posting, the higher the sales. In addition, it was confirmed through the cluster analysis that the influencer types for each product category were classified into four types and that there was a significant difference between groups according to sales. In other words, the implications of this study may suggest empirical solutions of social media sales strategies for influencers working on social media and marketers who want to use them as marketing tools.

Data Empowered Insights for Sustainability of Korean MNEs

  • PARK, Young-Eun
    • The Journal of Asian Finance, Economics and Business
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    • v.6 no.3
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    • pp.173-183
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    • 2019
  • This study aims to utilize big data contents of news and social media for developing a corporate strategy of multinational enterprises and their global decision-making through the data mining technique, especially text mining. In this paper, the data of 2 news media (BBC and CNN) and 2 social media (Facebook and Twitter) were collected for the three global leading Korean companies (Samsung, Hyundai Motor Company, and LG) from April, 2018 to April, 2019. The findings of this paper have shown that traditional news media and also modern social media have become devastating tools to extract global trends or phenomena for businesses. Moreover, this presents that a company can adopt a two-track strategy through two different types of media by deriving the key issues or trends from news media channels and also grasping consumers' sentiments, preference or issues of interest such as battery or design from social media. In addition, analyzing the texts of those media and understanding the association rules greatly contribute to the comparison between two different types of media channels to see the difference. Lastly, this provides meaningful and valuable data empowered insights to find a future direction comprehensively and develop a global strategy for sustainability of business.