• Asia pacific journal of information systems
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• 제34권1호
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• pp.191-208
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• 2024

This paper proposes the presence and importance of cultural differences to address user engagement in worldwide social media platforms. Based on Hofstede's cultural dimensions, this paper addresses their new meanings in the context of user engagement in social media. Our propositions address two research questions: (1) how do cultural dimensions, displayed on social media platforms, differ across national cultures?; (2) what different preferences the social media platforms have in terms of which cultural dimensions promote or suppress user engagement? User engagement in social media platforms is explained by the cultural differences in terms of the four cultural dimensions: individualism vs. collectivism, uncertainty avoidance, power distance, and masculinity vs. femininity. Implications are also discussed for research and practice.

• Asia pacific journal of information systems
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• 제30권4호
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• pp.785-807
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• 2020

The novel Coronavirus disease 2019 (COVID-19) is unprecedentedly changing the world since its outbreak in late 2019. Using the collected the data related to COVID-19 and the social media user data from a mobile application market research agency from January 25 to April 7, this study empirically examines the effect of the number of confirmed COVID-19 cases worldwide, the number news COVID-19, and the enforcement of social distancing measures on the daily active users (DAU) of two social media services - Twitter and Facebook - in South Korea. There are three important findings from the results of econometric analysis. First, the number of confirmed COVID-19 cases worldwide has a negative effect on the DAU of social media. Second, the number of COVID-19 news is negatively associated with the DAU of social media. Finally, the implementation of social distancing measures has no significant effect on the DAU of the social media. Theoretical implications and managerial guidelines are also discussed.

• The Journal of Asian Finance, Economics and Business
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• 제6권3호
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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.

• Journal of Korea Trade
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• 제24권8호
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• pp.39-62
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• 2020

Purpose - Korean exports account for a vast proportion of Korean GDP, and large volumes of Korean products are sold in the United States. Identifying and characterizing actual and potential product hazards related to Korean products is critical to safeguard Korean export trade, as severe quality issues can impair Korea's reputation and reduce global consumer confidence in Korean products. In this study, we develop country-of-origin-based product risk analysis methods for social media with a specific focus on Korean-labeled products, for the purpose of safeguarding Korean export trade. Design/methodology - We employed two social media datasets containing consumer-generated product reviews. Sentiment analysis is a popular text mining technique used to quantify the type and amount of emotion that is expressed in the text. It is a useful tool for gathering customer opinions regarding products. Findings - We document and discuss the specific potential risks found in Korean-labeled products and explain their implications for safeguarding Korean export trade. Finally, we analyze the false positive matches that arise from the established dictionaries that were used for risk discovery and utilize these classification errors to suggest opportunities for the future refinement of the associated automated text analytic methods. Originality/value - Various studies have used online feedback from social media to analyze product defects. However, none of them links their findings to trade promotion and the protection of a specific country's exports. Therefore, it is important to fill this research gap, which could help to safeguard export trade in Korea.

• Asian Journal of Business Environment
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• 제8권4호
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• pp.5-15
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• 2018

Purpose - The research aimed to reveal real decisional behavioral of management institutes in India for social media marketing usage, and analyses of empirical elements of social media consumption pattern. Research design, data, and methodology - The investigation was based around a research methodology using quantitative analysis with appropriate statistical techniques on random surveys of consumers, detailed exploratory and confirmatory factor analyses are applied to assess the empirical validity of the model and multiple regression employed using R studio edition to validate the reliability of the developed models. Results - A new conceptual framework is proposed - the management institutions decision model, providing a tool for effective and more focused decision-making strategies for developing better utilization techniques for social media. Management institutions have different requirements based upon objectives and resources available. The evidence suggests that the administrators need to be more aware of consumer indicators when targeting and designing social media marketing strategy. Conclusions - The research was based on samples and not the entire population of target consumers, providing limitations. As an inferential statistical method was chosen, the results might be susceptible to inaccuracy. The model developed from different age users, thereby providing rich perspectives into social media usage pattern.

• 무역학회지
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• 제47권6호
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• pp.21-37
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• 2022

This study sought to look at why Facebook and Twitter, which have dominated the social media market, are moving away from other services. To this end, we sought to identify the causes of churn in terms of firm-level strategic direction and resource allocation, which have not been actively presented to the studies. For this purpose, this study divides the social media firm's strategies into horizontal expansion strategy and vertical integration strategy based on the existing reports and researches, and how each of the representative firms' strategies affects users' switching behavior. As a result, there was a significant difference in the strategic direction of the social media firm, when a horizontal expansion strategy is taken, user's switching intention is higher than when a vertical integration strategy is taken. In addition, the switching intention according to the level of dependence showed that the lower the dependence on social media, the higher the intention to switch to other media. The findings are expected to provide highly realistic and concrete strategic alternatives for a variety of economic actors, such as individuals and companies who want to do business using social media.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.613-614
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• 2008

A content recommendation according to users preferences comes up in the Internet application due to contents overwhelming. This paper newly proposes a method to predict contents preference using tags in conjunction with Content-Based Filtering. By implementing this method, this paper cleans up the contents sparsity problem in Content-Based Filtering, and shows the outstanding improvements.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.30-39
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• 2022

This study investigates the influence of consumer needs pertaining to brand social media pages on the consumer brand attachment formation process. We collected 278 valid responses from females who have experienced the food brands' social media pages. Following the data analysis, we developed the results as follows. First, we examined the significant influence of attachment to brand social media page needs and socialization needs on consumer content consumption engagement and content contribution engagement on brand social media pages. Then we determined that consumer engagement significantly influenced consumer brand attachment. Finally, we found consumer consumption engagement exerted a significant mediation effect on the relationship between consumer needs and brand attachment. Based on the results, we outlined the potential theoretical and marketing strategy implications of this research.

• 지능정보연구
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• 제14권3호
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• pp.41-57
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• 2008

U-Publication은 독자가 기존의 출판물을 오프라인에서만 소비했던 것과는 달리, 여러 개의 자동인식태그가 부착되어 있어 자동인식태그 리더(reader)로 태그에 저장된 URL을 통해 온라인으로 접속할 수 있는 출판물을 말한다. U-Media를 기존의 미디어가 사람의 생체시스템에만 호소하는 것과 달리, 사람의 생체 시스템뿐만 아니라 사람에 내재되거나 사람이 가지고 있는 디지털 시스템에 호소하는 미디어라고 정의할 때(Lee & Ju 2007), U-Publication은 온라인과 오프라인이 Seamless하게 연결되어 양방향으로 정보가 이동할 수 있다는 측면에서 U-Media라고 할 수 있으며, 소비자들은 자동인식태그 부착 출판물의 인쇄된 컨텐트 뿐만 아니라 출판물에 부착된 태그의 링크를 통해서 추가적인 컨텐트를 소비할 수 있고 다양한 상거래를 할 수 있다. 이 논문은 U-Publication을 정의하고, 이를 기반으로 한 비즈니스 모델을 설계하고, 이 비즈니스 모델을 평가하는 과정을 시뮬레이션 방법에 의해 제시하고 있다.

• The Journal of Asian Finance, Economics and Business
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• 제8권3호
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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.