• Information Systems Review
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• v.21 no.2
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• pp.117-137
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• 2019

In the Big Data era, data science has become popular with the production of numerous data in various domains, and the power of data has become a competitive power. There is a growing interest in unstructured data, which accounts for more than 80% of the world's data. Along with the everyday use of social media, most of the unstructured data is in the form of text data and plays an important role in various areas such as marketing, finance, and distribution. However, text mining using social media is difficult to access and difficult to use compared to data mining using numerical data. Thus, this study aims to develop Korean Natural Language Application (KoALA) as an integrated application for easy and handy social media text mining without relying on programming language or high-level hardware or solution. KoALA is a specialized application for social media text mining. It is an integrated application that can analyze both Korean and English. KoALA handles the entire process from data collection to preprocessing, analysis and visualization. This paper describes the process of designing, implementing, and applying KoALA applications using the design science methodology. Lastly, we will discuss practical use of KoALA through a block-chain business case. Through this paper, we hope to popularize social media text mining and utilize it for practical and academic use in various domains.

• Journal of dental hygiene science
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• v.21 no.4
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• pp.260-266
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• 2021

Background: The purpose of the study was to evaluate the relationship and route of dental Social Media marketing by age group and support effective dental marketingy by age group. Methods: A study was conducted on 265 people, aged 20 to 64 years, who lived in Seoul, Gyeonggi area and regularly used one or more of the social media platforms, Naver Band, Facebook, Instagram, KakaoStory, Twitter, or YouTube more than once a day. A 27-question questionnaire survey of approximately 10 minutes was conducted, and the collected data was statistically analyzed using the PASW program, with the significane level set to 0.05. Results: "Introduction of acquaintances" was the most common route to visit the dentist. Regarding the use of social media platforms based on age group, 'Instagram' had the highest frequency among people belonging to the age groups of 20 to 29 years and 30 to 39 years; 'YouTube' had the highest frequency among those aged 40 to 49 years; and 'Naver Band' had the highest frequency among those aged 50 to 65 years. Conclusion: The most frequently used social media by consumers according to age included Facebook, YouTube, and Instagram. However, social media was found to have no significant impact on the choice of dental institutions, as the number of people who visited the dentist through "Introduction of acquaintances" was the highest, and "Introduction of acquaintances" did not have experience accessing the dentist site after dental marketing. If this study could provide customized marketing information for each age group through social media, it is expected that the marketing effect of dental institutions through social media would be maximized in the future.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.337-351
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• 2022

With the full spread and rapid development of social media, the trend of decentralization of social media information propagation is becoming clearer day by day, and the segmentation of time by audiences using social media information is clearly progressing. Therefore, this study aims to study the influence relationship between social media attitudes toward fake news, social capital, risk perception, and discriminant intentions based on existing studies. Accordingly, the research model presented related research questions and organized a questionnaire to collect a total of 500 valid surveys. The SPSS 26.0 program and the AMOS 24.0 program were used to analyze the data. The research results are as follows. First, the more positive the user's attitude towards the fake news identification intention of social media, the more they want to use various methods or tools to identify the authenticity of online information. Second, the more positive the user's attitude towards social media fake news, the more aware of the potential threats social media fake news poses to their own physical, psychological, financial and so on. At the same time, by raising one's own awareness of the dangers, counterintelligence intentions against fake news on social media will also increase. Third, the richer the social capital the user has, the stronger the information literacy, and therefore the stronger the identification intention of social media fake news. Fourth, the higher the value of social capital Chinese users have, the greater the damage they have suffered from fake news, and the higher the risk awareness of fake news to protect their interests. Fifth, it means that Chinese users recognized information suspected of social media and took corresponding measures.

• Human Ecology Research
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• v.59 no.1
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• pp.23-43
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• 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.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.145-150
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• 2020

It needs to explain the relationship between influencers and consequences to use continuity of social media. To address this question, we have developed an framework and made hypotheses to explicate and analyze influencers(social presence, perceived privacy risk, perceived enjoyment, commitment, and community identification) to the attitude and continuity of social media. To test empirically, data collected from on and line survey and resolved by structural equation model. We found that social presence, perceived enjoyment and commitment influence to the attitude and continuity of social media. Finally, the theoretical and practical implications of theses results are discussed also research limitation and future research directions.

• Genomics & Informatics
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• v.18 no.2
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• pp.17.1-17.4
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• 2020

The amount of content on social media platforms such as Twitter is expanding rapidly. Simultaneously, the lack of patient information seriously hinders the diagnosis and treatment of rare/intractable diseases. However, these patient communities are especially active on social media. Data from social media could serve as a source of patient-centric knowledge for these diseases complementary to the information collected in clinical settings and patient registries, and may also have potential for research use. To explore this question, we attempted to extract patient-centric knowledge from social media as a task for the 3-day Biomedical Linked Annotation Hackathon 6 (BLAH6). We selected amyotrophic lateral sclerosis and multiple sclerosis as use cases of rare and intractable diseases, respectively, and we extracted patient histories related to these health conditions from Twitter. Four diagnosed patients for each disease were selected. From the user timelines of these eight patients, we extracted tweets that might be related to health conditions. Based on our experiment, we show that our approach has considerable potential, although we identified problems that should be addressed in future attempts to mine information about rare/intractable diseases from Twitter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.391-406
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• 2015

Social media have emerged as new communication channels between consumers and companies that generate a large volume of unstructured text data. This social media content, which contains consumers' opinions and interests, is recognized as valuable material from which businesses can mine useful information; consequently, many researchers have reported on opinion-mining frameworks, methods, techniques, and tools for business intelligence over various industries. These studies sometimes focused on how to use opinion mining in business fields or emphasized methods of analyzing content to achieve results that are more accurate. They also considered how to visualize the results to ensure easier understanding. However, we found that such approaches are often technically complex and insufficiently user-friendly to help with business decisions and planning. Therefore, in this study we attempt to formulate a more comprehensive and practical methodology to conduct social media opinion mining and apply our methodology to a case study of the oldest instant noodle product in Korea. We also present graphical tools and visualized outputs that include volume and sentiment graphs, time-series graphs, a topic word cloud, a heat map, and a valence tree map with a classification. Our resources are from public-domain social media content such as blogs, forum messages, and news articles that we analyze with natural language processing, statistics, and graphics packages in the freeware R project environment. We believe our methodology and visualization outputs can provide a practical and reliable guide for immediate use, not just in the food industry but other industries as well.

• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.113-120
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• 2016

People use social media platforms such as Twitter to leave traces of their personal thoughts and opinions. In other words, social media platforms retain the emotions of the people as it is, and accurately understanding the emotions of the people through social media will be used as a significant index for disaster management. In this research, emotion type modeling method and emotional quotient quantification method will be proposed to understand the emotions present in social media platforms. Emotion types are primarily analyzed based on 3 major emotions of affirmation, caution, and observation. Then, in order to understand the public's emotional progress according to the progress of disaster or accident and government response in detail, negative emotions are broken down into anxiety, seriousness, sadness, and complaint to enhance the analysis. Ultimately, positive emotions are further broken down into 3 more emotions, and Russell emotion model was used as a reference to develop a model of 8 primary emotions in order to acquire an overall understanding of the public's emotions. Then, the emotional quotient of each emotion was quantified. Based on the results, overall emotional status of the public is monitored, and in the event of a disaster, the public's emotional fluctuation rate could be quantitatively observed.

• Korean Journal of Childcare and Education
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• v.14 no.6
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• pp.187-203
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• 2018

Objective: This study aimed to examine the mediating effect of mothers' parenting stress on the relationship between their self-differentiation and the tendency of addiction to social media. Methods: The participants in this study were two hundred and eight mothers with children aged 36 months or younger. Data were analyzed statistically using frequency, Pearson's correlation coefficients, and hierarchical multiple regression analysis. Results: The results of the present study are as follows. First, the mothers' self-differentiation was negatively associated with their parenting stress and social media addiction tendency. Second, both the total scores of the mothers' parenting stress and their distress were found to partially mediate the relationship between their self-differentiation and social media addiction tendency. However, the mothers' daily stress did not mediate the relationship between the variables. Conclusion/Implications: The findings of the current study have implications for developing ways of intervening in mothers' social media addiction tendency by reducing their parenting stress, particularly for mothers with low levels of self-differentiation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.187-198
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• 2021

The objective of this study is to examine the direct and indirect influences of government's role, organizational commitment, and media exposure on the corporate social and environmental responsibility disclosure (CSERD) of 42 Indonesian state-owned enterprises (SOEs) with good corporate governance as the mediator. This study uses a quantitative approach with path analysis to test the hypothesis. The sample in this study was directors of 42 state-owned enterprises in Indonesia. The data was collected using a questionnaire with items assessed on a five-point Likert scale. This study finds that 1) the government's role, organizational commitment, and media exposure have direct influences on good corporate governance and corporate social responsibility disclosure; 2) the government's role and organizational commitment have significant influences on corporate social and environmental responsibility disclosure with the mediation of good corporate governance, indicating that government's role and the organizational commitment are factors affecting Indonesian state-owned enterprises; and 3) the media exposure through good corporate governance mediation does not have a significant effect on corporate social and environmental responsibility disclosure. This means that media exposure is only one of the tools for CSERD, while SOEs have no obligation to disclose CSER through website or printed media.