• Journal of Distribution Science
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• v.18 no.4
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• pp.61-72
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• 2020

Purpose: Usage of leisure-sport social media would lengthen and strengthen the effects of positive event experiences on WOM behavior. This study is to examine the extent to which leisure sport social media use has the moderating potential to enhance the direction of the relationship between post-event emotions and event WOM behavior. Research design, data and methodology: A running event located in a major metropolitan area in the southeastern United States was selected. Participants of the running events completed the survey. Descriptive analysis and correlations between primary variables of interest were conducted. To examine interactions within the context of moderated regression, a hierarchical regression analysis was employed. Results: The results confirmed direct effects of a sense of achievement and event satisfaction on event WOM intention, supporting H 1 and H2. In specific, result revealed that the amount of time spending on social media for running content moderated the effect of a sense of achievement on event WOM intention, supporting H3, however, H4 was rejected. Conclusions: There are managerial implications of these results, particularly which pertain to how organizers may be able to use perceived benefits (i.e., a sense of achievement and satisfaction) and social media to increase positive WOM intention.

• Journal of the Korea Fashion and Costume Design Association
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• v.16 no.3
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• pp.33-48
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• 2014

Based on the advent and dissemination of new developments concerning information & telecommunications technology, web services have brought new paradigms into society, thus facilitating the birth and evolution of various service industries to society as a whole. This study is aimed at investigating the expansion of the first Birthday party culture and design examples of the first Birthday partywear appearing in social media, through an inquiry into the communication functions inherent in social media. Also, the development of the first Birthday partywear designs for women aged 20 to 30 years was accomplished by categorically analyzing design characteristics in preferred fashion styles uploaded and shared within online childcare communities. First, it can be concluded that due to the bidirectional flow of information between corporations and consumers occurring from the expansion of social media, the entire structure of the market is undergoing great changes. Next, the need for the supply of professionalized the first Birthday partywear can be proved by the influx of party planners and caterers into this new industry. Third, Through a categorical analysis of these 523 photos, elegance style was the most preferred while classic and romantic styles followed. Last of all, 5 pieces of partywear reflecting contemporary consumer lifestyles which focus on 'enjoying one's own life' were created under the concept of 'Romantic chic'. The created designs aim to present a style which follows the predominant trend of elegance, classic and romantic, whilst keeping sensitivity in moderation. In this context, this study has aimed to present fundamental research data in the field of online the first Birthday partywear, through the development of the first Birthday partywear design based on the first Birthday party consumer characteristics gleaned from various forms of social media.

• Information Systems Review
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• v.22 no.4
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• pp.93-113
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• 2020

This study investigates how the users' perceptions on like function in social media affect their attitudes toward the number of likes they receive from others. People conveniently believe that the number of likes is a significant measure of their online content quality and popularity. However, we take an ambivalent view that people do not settle their perceptions on the likes but change their like assessments according to circumstances. Specifically, we propose a model wherein emotional responses to the received likes may affect the value assessment of the likes. Our model shows how people resolve their internal contradiction on the value of the likes by flipping the traditional cognition-to-emotion mechanism to emotion-to-cognition mechanism. We validate the reversed dynamics between judgements and feelings using the data collected from 548 social media users. Results confirm that social media users' attitudes toward likes is largely affected by their emotional responses to their received number of likes. The implications of this study explain social media users' ambivalent attitudes toward likes by showing how they adjust their individual like valuation using their emotional responses.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.583-600
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• 2014

Social media is considered a valuable platform for gathering and analyzing the collective and subconscious opinions of people in Internet and mobile environments, where they express, explicitly and implicitly, their daily preferences for brands and products. Extracting and tracking the various attitudes and concerns that people express through social media could enable us to categorize brands and decipher individuals' cognitive decision-making structure in their choice of brands. We investigate the cognitive network structure of consumers by building an inter-category map through the mining of big data. In so doing, we create an improved online recommendation model. Building on economic sociology theory, we suggest a framework for revealing collective preference by analyzing the patterns of brand names that users frequently mention in the online public sphere. We expect that our study will be useful for those conducting theoretical research on digital marketing strategies and doing practical work on branding strategies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.9-15
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• 2018

This study is intended to investigate that it is possible to analyze the public awareness and satisfaction of the weather forecast service provided by the Korea Meteorological Administration (KMA) through social media data as a way to overcome limitations of the questionnaire-based survey in the previous research. Sentiment analysis and association rule mining were used for Twitter data containing opinions about the weather forecast service. As a result of sentiment analysis, the frequency of negative opinions was very high, about 75%, relative to positive opinions because of the nature of public services. The detailed analysis shows that a large portion of users are dissatisfied with precipitation forecast and that it is needed to analyze the two kinds of error types of the precipitation forecast, namely, 'False alarm' and 'Miss' in more detail. Therefore, association rule mining was performed on negative tweets for each of these error types. As a result, it was found that a considerable number of complaints occurred when preventive actions were useless because the forecast predicting rain had a 'False alarm' error. In addition, this study found that people's dissatisfaction increased when they experienced inconveniences due to either unpredictable high winds and heavy rains in summer or severe cold in winter, which were missed by weather forecast. This study suggests that the analysis of social media data can provide detailed information about forecast users' opinion in almost real time, which is impossible through survey or interview.

• Genomics & Informatics
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• v.19 no.3
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• pp.21.1-21.5
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• 2021

The use of social media data, like Twitter, for biomedical research has been gradually increasing over the years. With the coronavirus disease 2019 (COVID-19) pandemic, researchers have turned to more non-traditional sources of clinical data to characterize the disease in near-real time, study the societal implications of interventions, as well as the sequelae that recovered COVID-19 cases present. However, manually curated social media datasets are difficult to come by due to the expensive costs of manual annotation and the efforts needed to identify the correct texts. When datasets are available, they are usually very small and their annotations don't generalize well over time or to larger sets of documents. As part of the 2021 Biomedical Linked Annotation Hackathon, we release our dataset of over 120 million automatically annotated tweets for biomedical research purposes. Incorporating best-practices, we identify tweets with potentially high clinical relevance. We evaluated our work by comparing several SpaCy-based annotation frameworks against a manually annotated gold-standard dataset. Selecting the best method to use for automatic annotation, we then annotated 120 million tweets and released them publicly for future downstream usage within the biomedical domain.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1016-1025
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• 2015

This study tried to identify the influential users of college sports teams' Twitter accounts and categorize them into three groups including an official account, media account, and layperson account. A total of 14 Twitter accounts at NCAA Division 1 universities were selected through convenience sampling method. In men's sports, the greatest number of influential users was layperson account followed by media account and official account. In women's sports, the greatest number of influential users was layperson account followed by official account and media account. The results provided the insight of college sports online social network and will expand the growing literature on social media in sport and offer practical data for marketers to use social media more effectively.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.247-253
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• 2020

It has emerged Food-content among various forms of 1-person media through social media. Food-content influencer also market products through 1-person media, generating revenue through increased views and subscribers of 1-person media. It also sells products through sponsorship. In general, there is a profit structure through 1-person media viewing, but research on how restaurant companies generate profits directly through food-content is insufficient. In addition, research on converting subscribers to consumers through food-contents is minimal. In this paper, we propose an experiential application system based on the behavior of food-content creators. The proposed system collects and categorizes food-content information, and maps between highly related words to organize into keyword categories. The ontology tag-based concept network applied to the proposed system connects representative information by pre-extracting/mapping information related to information requests among a wide range of data. This method maps relevant food-content information to provide the user with data collected/storage in the form of an application. The user uses the application while watching the food eaten by the influencer and creator. And, it is meaningful that the user could be provided is provided with information about the food they want to eat.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.68-74
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• 2023

The food industry has been hit hard since the first outbreak of COVID-19 in 2019. However, as of April 2022, social distancing has been resolved and the restaurant industry has gradually recovered, interest in restaurant start-ups is increasing. Therefore, in this paper, 'restaurant start-up' was cited as a key keyword through social media big data analysis using TexTom, and word frequency and cone analysis were conducted for big data analysis. The keyword collection period was selected from May 1, 2022, when social distancing due to COVID-19 was lifted, to May 23, 2023, and based on this, a plan to develop chatbot services for restaurant start-ups was proposed. This paper was prepared in consideration of what to consider when starting a restaurant and a chatbot service that allows prospective restaurant founders to receive information more conveniently. Based on these analysis results, we expected to contribute to the process of developing chatbots for prospective restaurant founders in the future

• Fashion & Textile Research Journal
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• v.18 no.6
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• pp.858-868
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• 2016

This study aims to examine the formative characteristics of seniors' fashion in overseas social media, and look into the psychological characteristics of seniors by analyzing the emotions and the characteristics of psychological mechanism in seniors' fashion. The study methods include statistical analysis and content analysis for literary study and data analysis. For data analysis, statistical and content analyses were conducted to analyze 992 data collected from Advanced style, Facebook, and Instagram for 4 years from 2013 to 2016. In formative features shown at overseas social media, circle and square silhouette, achromatic color and warm color, showy tone color, soft material, horizontal details, plain and natural patterns, cap and sunglasses production, and sophisticated elegance styles appeared high. The emotional characteristics in senior's fashion had a silhouette that expressed stability, color that expressed passion, love, happiness, joy, hope and comfort. Materials were expressed by the emotions of dependence and attachment, details were expressed by stable, maternal, calm, comfortable and harmonious emotions. Patterns were expressed by the images of beauty, love, fruit and psychological stability. Accessories were expressed by young and characterful images. Style expressed the emotions of trust, pride, longing, intoxication and ecstasy. The characteristics of psychological mechanism used such shapes and patterns as flower, heart and lips to symbolize the emotions of love, humor, and fun. Young and trendy fashion were expressed in compensation for aging. Kitsch and kidult style was expressed by regression. Elegance fashion was expressed by the sublimation of pride, trust and intoxication.