• 아태비즈니스연구
• /
• 제12권2호
• /
• pp.161-174
• /
• 2021

Purpose - The purpose of this study was to examine the recent popular consumption trend, the hocance phenomenon, using social media big data. The study intended to present practical directions and marketing measures for the recovery and growth of the hotel industry after COVID-19 pandemic. Design/methodology/approach - Big data analysis has been used in various fields, and in this study, it was used to understand the hocance phenomenon. For three years from January 1, 2018 to December 31, 2020, we collected text data including the keyword 'hocance' from the blog and cafe of NAVER and Daum. TEXTOM and UCINET 6 were used to collect and analyze the data. Findings - According to the results of analysis, the words such as 'hocance', 'hotel', 'Seoul', 'travel', 'swimming pool', 'Incheon', 'breakfast', 'child' and 'friend' were identified with high frequency. The results of CONCOR analysis showed similar results in all three years. It has been confirmed that 'swimming pool', 'breakfast', 'child' and 'friend' are important when deciding on the hocance package. Research implications or Originality - The study was differentiated in that it used social media big data instead of traditional research methods. Furthermore, it reflected social phenomena as a consumption trend so there was practical value in establishing marketing strategies for the tourism and hotel industry.

• Journal of applied mathematics & informatics
• /
• 제41권5호
• /
• pp.1129-1143
• /
• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• 한국빅데이터학회지
• /
• 제4권1호
• /
• pp.99-118
• /
• 2019

본 연구는 소셜 미디어 참여 관련 연구 베타분석을 위해 네트워크 분석과 클러스터링 기법을 활용하였다. 주경로 분석 결과 37개의 주요 연구가 추출되었고 커뮤니티 관련 네트워크와 뉴 미디어 관련 네트워크 두 가지로 구분되었다. 연결망 분석과 클러스터링 결과 네가지 클러스터가 형성되었다. 본 연구는 학술 데이터를 활용해 연구 동향을 거시적으로 파악하며 그 방법론으로 네트워크 분석과 기계학습을 활용하였다는 학술적 의의를 가진다.

• 한국정보시스템학회지:정보시스템연구
• /
• 제23권4호
• /
• pp.1-24
• /
• 2014

This study is intended to examine two issues related with social media messages. At first, the authors investigate that how they can categorize messages in the social media and how corporate twitters and brand twitters communicate with consumers. Secondly, after dividing messages in the social media into several groups, the authors investigate how each type of messages differ one another in terms of the consumer response. For examining these research issues, the authors gather twitter message data of global top 100 brands and categorize messages into 5 types (i.e., interactivity, diversion, information sharing, promotional, content) based on the motivation of communication and the format of the messages. Especially, the authors use content analysis methodology, which is normally used as the qualitative approach, in order to identify the type of messages. Furthermore, the authors present interactivity type of messages can communicate better with consumers and induce more favorable responses from consumers in the social media than any other type of messages. This research can provide implications in terms of theoretical, methodological, and managerial perspective.

• International Journal of Contents
• /
• 제17권1호
• /
• pp.1-10
• /
• 2021

Visual analytics is an emerging research field that combines the strength of electronic data processing and human intuition-based social background knowledge. This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain. We comparatively investigated the sentiment flow over time and language usage patterns between companies with a good reputation and firms with a poor reputation. In addition, this study explored the relations between reputation and marketing communication strategies. We found that cryptocurrency firms more actively produced information when there was an increased public demand and increased transactions and when the coins' prices were high. Emotional language strategies on social media did not affect cryptocurrencies' reputations. The pattern in semantic representations of keywords was similar between companies with a good reputation and firms with a poor reputation. However, the reputable firms communicated on a wide range of topics and used more culturally focused strategies, and took more advantages of social media marketing by expanding their outreach to other social media networks. The visual big data analytics provides insights into business intelligence that helps informed policies.

• 아태비즈니스연구
• /
• 제12권1호
• /
• pp.41-56
• /
• 2021

Purpose - This empirical study examined the influence of post-communist countries sociol-political factor of freedom of expression preconditioning, and trust in agency, mediating performance expectancy of social media users representing the citizens' behavioural intention to utilize social media in a post-communist country, the case of Mongolia. Design/methodology/approach - This research collected 403 valid survey data from citizens those who use social media in Mongolia. The study used Partial Least Squire (PLS) analysis with the research conceptual model founded on the UTAUT model. Findings - The study shown that citizens in post-communist, they strongly willing freedom of expression, which driving as a positive precondition factor, and this has an indirect positive influence, and trust in agency mediates to enhance performance expectancy. Social influence, and effort expectancy factors have direct positive influence on the intention to use of social media systems in the public sector domain of Mongolia. Research implications or Originality - This research proposed a new model to test citizens' intention to use social media as a communication tool to engage with public organizations in the pre-adoption stage of post-communist countries. Theoretically, this research builds up to the unique theoretical contribution with social media by examining a new social media-based third-party intercommunication medium, incorporating intent to utilize for citizens with government in post-communist countries. Practically, this article lays out the directions to aid social media usage for government sector with concerning citizens intentions in the post-communist situation.

• Journal of Contemporary Eastern Asia
• /
• 제18권1호
• /
• pp.49-69
• /
• 2019

Over the last couple of years, digital diplomacy has become a fascinating area of research among Mass Communication, Peace and Conflict Studies, and International Affairs scholars. Social media and new technology open up new avenues for governments, individuals, and organizations to engage with foreign audiences. However, developing countries' governments are still lacking in the realization of the potential of social media. This study aims to analyze the usage of social media (Facebook & Twitter) by the two biggest countries in South Asia (Pakistan and India). I selected 10 government officials' social media accounts including prime ministers', national press offices', military public relations offices', public diplomacy divisions', and ministries of foreign offices' profiles. The study relies on quantitative content analysis and a comparative research approach. The total number of analyzed Twitter tweets (n=1,015) and Facebook posts (n=1,005) include 10 accounts, five from each country. In light of Kent and Taylor's (1998) dialogic communication framework, the results indicate that no digital engagement and dialogue occurs between government departments and the public through social networking sites. Government departments do not engage with local or foreign audiences through digital media. When comparing both countries, results reveal that India has more institutionalized and organized digital diplomacy. In terms of departmental use of social media, the digital diplomacy division and foreign office of India is more active than other government departments in that nation. Meanwhile, Pakistan's military public relations office and press office is more active than its other government departments. In conclusion, both countries realize the potential of social media in digital diplomacy, but still lack engagement with foreign audiences.

• International Journal of Computer Science & Network Security
• /
• 제22권9호
• /
• pp.7-14
• /
• 2022

COVID-19 has caused a global disturbance, increased anxiety, and panic, eliciting diverse reactions. While its cure has not been discovered, new infection cases and fatalities are being recorded daily. The focus of the present study was to analyze the reaction of gifted undergraduate students on social media during the quarantine period of the COVID-19. A special group of gifted students, who joined the program of attracting and nurturing talents at the University of Jeddah, University students as were the target sample of this study. To analyze online reactions during the pandemic; the choice of university students was arrived at as they are perceived to be gifted academically. Hence, the analysis of the impacts on their behavior on social media use is imperative. This study presented accurate and consistent data on the effects of social media using Twitter platforms on gifted students during the quarantine occasioned by the COVID-19 pandemic. The behavior of learners due to during the use of social media was extensively explored and results analyzed. The study was carried out between April and May 2020 (quarantine period in Saudi Arabia) to establish whether the online behavior of gifted students reflects positive or negative feelings. The methods used in conducting this study the research were online interviews and scraping participants' Twitter accounts (where most of the online activities and studies take place). The study employed the Activity theory to analyze the behavior of gifted students on social media. The sample size used was 60 students, and the analysis of their behavior was based on Activity theory Overall, the results showed proactive, positive behavior for coping with a challenging situation, educating society, and entertaining. Finally, this study recommends investing in gifted students due to their valuable problem-solving skills that can help handle global pandemics efficiently.

• 복식문화연구
• /
• 제25권6호
• /
• pp.928-942
• /
• 2017

Social media has become an integral part of consumers' daily lives. Individuals connect with one another on social networking sites to like, share, and post information and experiences. As social media become popular among millennials, a growing number of fashion retailers use social media networks in the context of online commerce transactions. Accordingly, an increased number of fashion retailers has been using social media as an advertising tool and a retail channel. Despite the popularity of social media among millennials, empirical findings are limited to reveal factors associated with young consumers' intentions to use social commerce in fashion shopping. This study sought to examine factors affecting millennials' intentions to use social commerce in fashion shopping by adopting the technology acceptance model. A total of 524 college students completed an online survey in the U.S. The results of structural equation model confirmed that perceived ease of use, usefulness, and enjoyment had a positive impact on millennials' attitudes and intentions toward fashion shopping in social commerce. While both perceived ease of use and usefulness positively influenced enjoyment, usefulness had a stronger impact than ease of use. Compared to usefulness, enjoyment had much stronger impact on attitudes. Further structural model analysis revealed a direct, positive influence of perceived usefulness of social commerce on perceived enjoyment of social commerce, which has not been explored in prior studies. These findings provide theoretical and managerial implications.

• Human Ecology Research
• /
• 제59권1호
• /
• pp.23-43
• /
• 2021

This study looked through the text mining analysis to check the status of the virtual assistant service, and explore the needs of consumers, and present consumer-oriented directions. Trendup 4.0 was used to analyze the keywords of AI services in Online News and social media from 2016 to 2020. The R program was used to collect consumer comment data and implement Topic Modeling analysis. According to the analysis, the number of mentions of AI services in mass media and social media has steadily increased. The Sentimental Analysis showed consumers were feeling positive about AI services in terms of useful and convenient functional and emotional aspects such as pleasure and interest. However, consumers were also experiencing complexity and difficulty with AI services and had concerns and fears about the use of AI services in the early stages of their introduction. The results of the consumer review analysis showed that there were topics(Technical Requirements) related to technology and the access process for the AI services to be provided, and topics (Consumer Request) expressed negative feelings about AI services, and topics(Consumer Life Support Area) about specific functions in the use of AI services. Text mining analysis enable this study to confirm consumer expectations or concerns about AI service, and to examine areas of service support that consumers experienced. The review data on each platform also revealed that the potential needs of consumers could be met by expanding the scope of support services and applying platform-specific strengths to provide differentiated services.