• Journal of Digital Contents Society
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• v.18 no.3
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• pp.567-575
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• 2017

Location-based services play an important role in many applications such as disaster warning systems and recommendation systems. These applications often require not only location information (e.g., name, latitude, longitude, etc.) but also the impact of events (e.g., earthquake, typhoon, etc.) on locations. Recently, to provide the impact of an event on a location, how to calculate location trustiness by using multimodal information such as earthquake information and disaster sensor data is researched. In the previous approach, the linear decrement of impact value of an event is applied to obtain the location trustiness of a specific location. In this paper, we propose a new approach to enrich location trustiness, that is, the impact of an event on a location, by using social media information additionally. Firstly, we design a collecting system for earthquake information and social media data. Secondly, we present an approach of location trustiness calculation based on earthquake information. Finally, we propose a new approach to enrich location trustiness by augmenting the trustiness in spatially distributed manner based on social media.

• Human Ecology Research
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• v.58 no.4
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• pp.613-633
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• 2020

This study identifies consumers' perceived benefits and costs when using Samsung Health (a healthcare app) based on consumer reviews from Google Play Store's app and social media discourse. We examine the differences in the benefits and the costs of Samsung Health using these two sources of data. We conducted text frequency analysis, clustering analysis, and semantic network analysis using R programming. The major findings are as follows. First, consumers experience benefits and costs on several functions of the app, such as step counting, device interlocking, information acquisition, and competition with global consumers. Second, the results of semantic network analysis showed that there were eight benefit factors and three cost factors. We also found that the three costs correspond to the benefits, indicating that some consumers gained benefits from certain functions while others gained costs from the same functions. Third, the comparison between consumer app review and social media discourse showed that the former is appropriate to assess the performance of app functions, while the latter is appropriate to examine how the app is used in daily life and how consumers feel about it. The current study suggests managerial implications to healthcare app service providers regarding what they should strengthen and improve to enhance consumers' satisfaction. It also suggests some implications from the two media, which can be mutually complementary, for researchers who study consumer opinions.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.410-422
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• 2017

This study researches PDA (Paralingustic Digital Affordances) in the social media on the basis of Uses and Gratification theory. The study defines PDA as Likes in Facebook and Instagram and Favorites in Twitter. The study inquiries into the motivation of using PDA and interpretational way when Social media users play a role of a sender or a receiver. For this research purpose, the focus group and interview were conducted with 36 college student in the Korea metropolitan area. The research is to comprehend the motivation and satisfaction of using PDA by applying structured theory frame of Uses and Gratification. As a result, it contributes to more satisfactions when PDA users interact each other as a sender and a receiver than mere verbal-communication. Furthermore, PDA in each social media has different meaning and gravity. For instance, Likes in Instagram is considered less important and lighter than Likes in Facebook. Moreover, people use the PDA without any restriction. People favorably use PDA most of the time, but sometimes they use in contradictory or sarcastic way.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.133-140
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• 2020

Emotional analysis is an application of opinion mining that analyzes opinions and tendencies of people appearing in unstructured text. Recently, emotional analysis of social media has attracted attention, but social media contains newly-created words and slang, so it is not easy to analyze with existing emotional analysis. In this study, I design a new emotional analysis system to solve these problems. The proposed system is possible to analyze various emotions as well as positive and negative in social media including newly-created words and slang. First, I collect newly-created words and slang related to emotions that appear in social media. Then, expand the existing emotional model and use it to quantify the degree of sentiment in emotional words. Also, a new sentiment dictionary is constructed by reflecting the degree of sentiment. Finally, I design an emotional analysis system that applies an sentiment dictionary that includes newly-created words and an extended emotional model.

• Journal of Korea Trade
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• v.24 no.8
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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.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.105-110
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• 2021

In this work, we design and implement a prototype of the mobile UX that works with blockchain-based smart contract systems so that artists and buyers who trade artworks through social media can find reliable trading partners and make secure transactions with each other. The developed prototype has the following characteristics. Utilizing prototypes, we cost-effectively validate the design of mobile UX(User Experience). First, we implement familiar UXs that social media users can use without additional explanation. Second, it is possible to check the reputation of the counterpart and encourage users to make fair deals that can increase their own reputation. Third, it implement the UX for common use by users around the world. Fourth, we design and implement to operate independently of the social media system.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.583-598
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• 2022

This study is a follow-up study of the Social Media Emotional Contagion(SECS) and it aims to validate the Social Media Emotional Contagion Scale(SECS) through CFA and criterion-related validity. The data was collected from 326 people in 20s. The criterion-related validity of SECS were confirmed with the Korean version of the Emotional Contagion Scale(K-ECS), the Basic Empathy Scale in Adult(BES-A), and the Rosenberg Self-esteem Scale(SES). As a result, the K-ECS and sub-factor of Emotional Contagion of BES-A, which are the same as the construction of SECS, converged. Other scales were differentiated from SECS. However, sub-factor of SES of positive self-esteem, which are the same as the construction of SECS, converged. Also, sub-factor of SES of negative self-esteem, which are the same as the construction of SECS of negative Emotional Contagion, converged. Finally, the significance and limitations of this study and future studies were discussed.

• Journal of Distribution Science
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• v.20 no.5
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• pp.35-47
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• 2022

Purpose: To explain the effect of product quality, price perception, online distribution, and social media promotion on attitudes, customer satisfaction, and local brand love. Research design, data and methodology: The population of this study are Indonesians who have purchased local Indonesian brand products. The size of the sample used was 240 people with purposive sampling method. The analytical technique used is Path Analysis using SEM-PLS. Results: product quality, price perception, online distribution have a positive effect on attitudes, but social media promotion has a positive and insignificant effect on consumer attitudes; product quality, price perception, online distribution, and social media promotion have a positive and significant effect on customer satisfaction, and attitudes have a positive and significant effect on local brand love; and customer satisfaction has a positive effect on brand love for local brands. Conclusion: Therefore, it is important for local brand product businesses to pay attention to product quality, price perception, online distribution, and social media promotion in order to be able to build positive attitudes, customer satisfaction and ultimately have an impact on local brand love. In online distribution, with online distribution, it is easy for marketers to deliver multimedia content through online methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.175-184
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• 2023

Korean Wave is now internationalized through the internet by social media, which have no space-time restrictions. This research examine the continuance use of K-Pop promotion using social media in Indonesia. In this study we apply the Expectation-Confirmation Model to analyze the effects of individual self-efficacy and perceived enjoyment on perceived usefulness, confirmation, and satisfaction of Social Media. As a research method for that purpose, the conformity of the model and the research hypothesis were verified using the structural equation model. As a result, it was found that the perceived enjoyment positively influences perceived usefulness, self-efficacy has a positive influence on perceived usefulness. We also found that confirmation positively affects both perceived usefulness and satisfaction, and that perceived usefulness positively affects satisfaction. Finally, satisfaction was found to always have a positive effect on intention to use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1377-1393
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• 2023

Social media is used for various purposes including entertainment, communication, information search, and voicing their thoughts and concerns about a service, product, or issue. The social media data can be used for information mining and getting insights from it. The World Health Organization has listed COVID-19 as a global epidemic since 2020. People from every aspect of life as well as the entire health system have been severely impacted by this pandemic. Even now, after almost three years of the pandemic declaration, the fear caused by the COVID-19 virus leading to higher depression, stress, and anxiety levels has not been fully overcome. This has also triggered numerous kinds of discussions covering various aspects of the pandemic on the social media platforms. Among these aspects is the part focused on vaccines developed by different countries, their features and the advantages and disadvantages associated with each vaccine. Social media users often share their thoughts about vaccinations and vaccines. This data can be used to determine the popularity levels of vaccines, which can provide the producers with some insight for future decision making about their product. In this article, we used Twitter data for the vaccine popularity detection. We gathered data by scraping tweets about various vaccines from different countries. After that, various machine learning and deep learning models, i.e., naive bayes, decision tree, support vector machines, k-nearest neighbor, and deep neural network are used for sentiment analysis to determine the popularity of each vaccine. The results of experiments show that the proposed deep neural network model outperforms the other models by achieving 97.87% accuracy.