• Journal of Convergence Society for SMB
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• v.5 no.2
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• pp.27-32
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• 2015

Recently, service-related products have gained more attention than general products on the existing social commerce sites. Based on the situation, the effect that the service quality of social commerce has on customer satisfaction was analyzed in this study. It is a study that analyzes how much the service quality affects the customer satisfaction after the purchase, targeting consumers who have made purchases of social commerce products. In the case of social commerce, it is well-known that the diversity and convenience of products have a significant effect on customer satisfaction. Social commerce is currently being dumped beyond the 900 sites and dozens of cases of news, real-time searches of popular portal sites appeared not to be bored enough to related sites to drive the popularity coming quickly dug into our everyday lives of human beings. Yet the perception of social commerce seems not properly established because of the new concept was suddenly going to go through penetration without a collective interpretation and acceptance process. Most of the companies that often mimic the syoseol commerce is large, the blame did not depart from the forms of social shopping. We believe that personal and exhibit their skills and talents, and to wonder to see the social rather than the individuals who make unilateral companies.

• Korean journal of communication and information
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• v.46
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• pp.323-353
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• 2009

Press (un)fairness has been a social issue in Korea. The previous research focused mainly on the suggestion of fairness norms, principles, concepts, and definitions. Also, the research tried to measure the degree of fairness by analyzing press contents. This study attempted to overcome the media- and source-oriented approach proposing ordinary press consumers' perspectives. The study posited that one's fairness judgment would be greatly influenced by his or her preexisting attitudes on issue. Based on social judgment theory and hostile media perception framework, the research expected 'assimilation' bias for attitudinally congruent group and 'contrast' bias for attitudinally incongruent group. An $3\times3\times2$ experimental design was employed to test the theoretical predictions. The results found assimilation and contrast bias for strong attitude groups who read one-sided and two-sided messages. The results also implied hostile media perception occurred by selective categorization. Also the difficulty and limitation of traditional fairness judgment and media-centered approach was discussed.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.11-20
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• 2021

This study extracts topics related to university education through newspaper articles and analyzes the characteristics of each topic and the reporting patterns of each newspaper. The 9 topics were discovered using LDA. Topic 1 and Topic 3 are related to university support projects for education, but Topic 3 is focused on local universities. Topic 2 is about university education after COVID-19, Topic 4 teaching-learning methods, Topic 5 government policies, Topic 6 the high school education contribution university support projects, Topic 7 the university education vision, Topic 8 internationalization, and Topic 9 the entrance exam. The Chosun Ilbo, Kyunghyang, and Hankyoreh reported a lot of articles associated to lectures after COVID-19, government policies, and comments on university education. Relevant articles since 2016 have been analyzed by newspaper type and before/after COVID-19 through which differences in the topics were studied and discussed. These findings would suggest a basic policy guideline for university education and imply that the positive and negative effects of the media need to be considered.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.149-163
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• 2021

The 4th industrial revolution refers to the next-generation industrial revolution led by information and communication technologies such as artificial intelligence (AI), Internet of Things (IoT), robot technology, drones, autonomous driving and virtual reality (VR) and it also has made a significant impact on the development of the advertising industry. However, the world is rapidly changing to a non-contact, non-face-to-face living environment to prevent the spread of COVID 19. Accordingly, the role of the 4th industrial revolution and advertising is changing. Therefore, in this study, text analysis was performed using Big Kinds to examine the 4th industrial revolution and changes in advertising before and after COVID 19. Comparisons were made between 2019 before COVID 19 and 2020 after COVID 19. Main topics and documents were classified through LDA topic model analysis and Word2vec, a deep learning technique. As the result of the study showed that before COVID 19, policies, contents, AI, etc. appeared, but after COVID 19, the field gradually expanded to finance, advertising, and delivery services utilizing data. Further, education appeared as an important issue. In addition, if the use of advertising related to the 4th industrial revolution technology was mainstream before COVID 19, keywords such as participation, cooperation, and daily necessities, were more actively used for education on advanced technology, while talent cultivation appeared prominently. Thus, these research results are meaningful in suggesting a multifaceted strategy that can be applied theoretically and practically, while suggesting the future direction of advertising in the 4th industrial revolution after COVID 19.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.199-210
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• 2019

Virtual Advertising, which was introduced exclusively in sports casting programs in 2010, has enlarged its scope to terrestrial TV networks' sports news, entertainment shows, and dramas by 2015. Such advertising deregulation allows broadcasting business operators to insert more various virtual advertising methods into TV programs. Despite recent evaluation that virtual advertising was deregulated to a large degree, it is still inadequate compared to foreign state of affairs and has a lot of room for growth. Therefore, this research explores a literature review of virtual advertising in other countries and considers possible ways for virtual advertising in Korea to move forward. Additionally, through in-depth interview with seven virtual advertising experts, the research unravels positive and negative impacts of virtual advertising as well as its current state of affairs and struggles. This research also analyses the regulation of virtual advertising and finally explores possible revitalization strategies. The results of the research show that it is necessary to first improve the viewers' favorable concerning virtual advertising in order to revitalize virtual advertising. Revitalization will also require a clarification of regulation as well as a more unified and consistent content review and rating system. Furthermore, it is imperative that data of advertising impact will be accessible to advertisers and that advertising regulation will loosen. Revitalization will also require a clarification of regulation as well as a more unified and consistent content review and rating system. Furthermore, it is imperative that data of advertising impact will be accessible to advertisers and that advertising regulation will loosen. It is necessary to further develop new techniques and creators of virtual advertising. The research suggests strategies and alternative paths for the growth and revitalization of the virtual advertising market in light of recently revised law.

• Journal of Korea Entertainment Industry Association
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• v.15 no.6
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• pp.1-13
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• 2021

This study explored the mechanism by which Trot gained a superior position in the broadcasting contents market after the TV Chosun audition program was broadcast. We analyzed the narrative structure of the program to determine what differentiation and popularization strategy the trot audition program took from the existing audition program, and analyzed in-depth interviews with music experts and interviews with the production team. appealed to viewers with a strategy that reversed the success strategy of existing audition programs. First, the strong/non-competent participants did not compete with each other, but rather the strong/skilled players competed against each other. This trot audition set the singing ability as a new 'discourse on sincerity'. Second, we broke away from the 'demon editing', which was considered essential for audition programs, took a strategy of excluding villains. Third, we broke the practice of audition programs that were supposed to show expertise in specific genres, such as idol music, hip-hop, and bands, and combined trot with various genres. Fourth, unlike previous audition programs that mainly targeted specific generations or genders, the strategy was to expand the audience by targeting various age groups. Fifth, it has formed a middle-aged fandom with a 'subtitle strategy' that uses subtitles well to arouse viewers' interest and help empathize.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.97-109
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• 2024

In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.21-44
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• 2018

In recent years, the rapid development of internet technology and the popularization of smart devices have resulted in massive amounts of text data. Those text data were produced and distributed through various media platforms such as World Wide Web, Internet news feeds, microblog, and social media. However, this enormous amount of easily obtained information is lack of organization. Therefore, this problem has raised the interest of many researchers in order to manage this huge amount of information. Further, this problem also required professionals that are capable of classifying relevant information and hence text classification is introduced. Text classification is a challenging task in modern data analysis, which it needs to assign a text document into one or more predefined categories or classes. In text classification field, there are different kinds of techniques available such as K-Nearest Neighbor, Naïve Bayes Algorithm, Support Vector Machine, Decision Tree, and Artificial Neural Network. However, while dealing with huge amount of text data, model performance and accuracy becomes a challenge. According to the type of words used in the corpus and type of features created for classification, the performance of a text classification model can be varied. Most of the attempts are been made based on proposing a new algorithm or modifying an existing algorithm. This kind of research can be said already reached their certain limitations for further improvements. In this study, aside from proposing a new algorithm or modifying the algorithm, we focus on searching a way to modify the use of data. It is widely known that classifier performance is influenced by the quality of training data upon which this classifier is built. The real world datasets in most of the time contain noise, or in other words noisy data, these can actually affect the decision made by the classifiers built from these data. In this study, we consider that the data from different domains, which is heterogeneous data might have the characteristics of noise which can be utilized in the classification process. In order to build the classifier, machine learning algorithm is performed based on the assumption that the characteristics of training data and target data are the same or very similar to each other. However, in the case of unstructured data such as text, the features are determined according to the vocabularies included in the document. If the viewpoints of the learning data and target data are different, the features may be appearing different between these two data. In this study, we attempt to improve the classification accuracy by strengthening the robustness of the document classifier through artificially injecting the noise into the process of constructing the document classifier. With data coming from various kind of sources, these data are likely formatted differently. These cause difficulties for traditional machine learning algorithms because they are not developed to recognize different type of data representation at one time and to put them together in same generalization. Therefore, in order to utilize heterogeneous data in the learning process of document classifier, we apply semi-supervised learning in our study. However, unlabeled data might have the possibility to degrade the performance of the document classifier. Therefore, we further proposed a method called Rule Selection-Based Ensemble Semi-Supervised Learning Algorithm (RSESLA) to select only the documents that contributing to the accuracy improvement of the classifier. RSESLA creates multiple views by manipulating the features using different types of classification models and different types of heterogeneous data. The most confident classification rules will be selected and applied for the final decision making. In this paper, three different types of real-world data sources were used, which are news, twitter and blogs.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.203-217
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• 2018

The research objective of this study is to analyze the aspects of small group decision-making process based on reading news reports in the context of the socio-scientific issues (SSI) activity related to climate change. Twenty-two high school students from Gyeonggi Province, South Korea, were asked to read two news reports on the UN climate change conferences and take a stance on joining the Paris Agreement both as an individual and as a small group. The news reports were analyzed in terms of genre, discourse, and style adapting the critical discourse analysis (CDA) and the decision-making processes of the small groups were examined on recognizing a problem and evaluating alternatives and decisions. The results from analyzing the news reports denoted that the Paris agreement is not only related to finding ideal solutions to climate change, but rather, connected to political or economic interests and power relationship. In the stage of recognizing a problem, meanwhile, different frames which students recognize the Paris agreement and discourses in the foreground of the news reports were the critical causes in terms of identifying the problem. In the stage of evaluating alternatives and decisions, the equity and fairness were the criteria for the small group discussions. This study implies the necessity of the scientific literacy instruction to develop the ability to critical reading in the context of the SSI.