• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.1-11
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• 2023

Unlike in the past, when the demand for web content was increasing and the use behavior of watching short videos was changed, unlike the past when only TV dramas and differentiation were mentioned, web dramas are more firmly established through various attempts. A typical form change is commerce of web dramas. Recently, more and more cases have been produced in the form of product sales by securing real-time functioned, which are disadvantages of commerce, through web dramas. In this trend, web dramas are also increasing interest in product sales. This can be said to be a form developed from the concept of a company's PPL, and the number of companies that use web dramas that predict continuous growth as strategic product promotion and marketing means is continuously increasing. Therefore, this study provides basic data on consumer behavior to collect product information and purchase products using web dramas to companies that are using or considering web dramas, and through this, companies design and establish marketing strategies using web dramas.

• Educational Technology International
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• v.17 no.2
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• pp.273-305
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• 2016

The EBS teaching coaching program, '선생님이 달라졌어요' broadcasted about 30 dramatic teaching improvement cases. The TV program has gained great attention and been used widely as a good example for making some meaningful improvements in teaching. However, there has not been an attempt to research and gather the series beyond the individual coaching examples for the viewers (mainly teachers) to obtain more comprehensive educational insights of the results. This study, therefore, reviews the program and conveys how the overall coaching actually took place, examines changes in classrooms, and discusses the implications the results with theoretical foundations. The researcher selected 12 teachers' coaching cases among 30 ones. Then the reviewers reviewed the program with the 6 categories. According to the results, the coaching took place 6-8 months for each individual teacher. The common difficulty teachers shared was a big gap between teachers' effort for teaching versus 'students problematic behaviors' in class. The overall direction for the coaching solution was 'to improve the relationship with students' first rather than to mainly focus on teaching the content. Students changed and actively participated in the learning process when teachers improved their relationships with the students. The researcher discussed how building good relationships with students greatly affects the improvement in teaching with the 'Needs Hierarchy' and 'Brain Science' theories.

• Journal of the Korean Society of Food Culture
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• v.38 no.6
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• pp.373-380
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• 2023

In this study, 294 housewives in Siheung, Gyeonggi-do, were surveyed to evaluate the differences in the recognition and use of nutrition labeling according to age and to present data for nutrition education. The younger the age, the more aware the consumer was of the information on the nutrition label. Housewives who were younger than 60 years were more likely to check the nutrition labels. The lower the age, the higher the reliance on the nutritional labeling content of the food, and the higher the recognition level of nutritional labeling. It was found that the lower the age, the easier it was for the consumer to understand the nutritional labeling. Among housewives in their 30s and younger, 89.5 percent said they believed checking nutrition labels would help their health. In the younger age group knowledge and information on nutrition labeling was acquired from the internet, and in the older age group, knowledge was acquired from television, radio, and newspapers. Research conducted on housewives in other regions in the future could provide more detailed information suitable for the population of each region. This would serve as data for nutrition education on the recognition and use of nutrition labeling for a healthy diet.

• Journal of Nutrition and Health
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• v.54 no.4
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• pp.398-411
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• 2021

Purpose: The objective of this study was to investigate food and nutrition information utilization practices of adults aged between 20 and 30 years to provide the basic data for developing customized content. Methods: Statistical analyses were performed using the SPSS program (ver. 24.0) for the 𝛘²-test, t-test, one-way analysis of variance, and Duncan's multiple range test. Results: Of the 570 subjects surveyed, 45.4% were men, 54.6% were women, 66.3% were in their 20s, 33.7% were in their 30s, 41.4% were single-person households, and 58.6% lived with their families. On average, 14.2% of televisions (TVs), 26.0% of personal computers (PCs), and 63.7% of smartphones were used for more than three hours per day. 30.9% of respondents searched for food and nutrition information more than once a week. 70.0% of the respondents had then applied the information in real life and 54.7% of the respondents said they would share information with others. Information retrieval rate was in the order of 'restaurant (64.8%)', 'diet (57.5%)', and 'food recipes (55.7%)'. Overall satisfaction with food and nutrition information averaged 3.33 on a five-point scale. Satisfaction score was in the order of 'enough description and easy to understand (3.43)', 'matching title and content (3.35)', and 'providing new and novel information (3.22)'. Satisfaction scores were significantly higher in the group that searched for information (p < 0.001), the group that used the retrieved information in real life (p < 0.001), and the group that conveyed this information to others (p < 0.001). Conclusion: To improve information user satisfaction, it is necessary to provide customized information that fits the characteristics of information users. For this purpose, it is necessary to continuously conduct surveys and satisfaction evaluations for each target group.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.7
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• pp.127-138
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• 2012

Unlike the first generation of Korean Wave (Hallyu 1.0), which mainly refers to the exports of Korean TV dramas via broadcasting systems, the New Korean Wave (Hallyu 2.0) era has been brought by K-pop (Korean popular music) via the rapid growth of social media. The purpose of this study is to understand the impact of this significant shift in media on global fans and their way of adopting Korean cultural goods from a social capital perspective, in order to draw some implications for the current Korean content industries. Most global fans of K-pop are young and use social media to access digital content and share their opinions spontaneously. SNS providers such as YouTube and Facebook not only act as information providers to usher the fans to online music retailers; but also function as links between these fans and cultural producers by turning bonding social capital into bridging social capital. Telecommunication and advertising companies participate in this market as a third party by providing funds for supporting digital circulation and distribution. In this multi-sided market with the interdependent agents, it is extremely important to secure a platform that leads the evolution of its business ecology. Without owning the platform, there is also a very little chance to produce linking social capital as a means to maximize the impact of New Korean Wave.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.97-117
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• 2012

Nowadays, Internet users tend to do a variety of actions at the same time such as web browsing, social networking and multimedia consumption. While watching a video, once a user is interested in any product, the user has to do information searches to get to know more about the product. With a conventional approach, user has to search it separately with search engines like Bing or Google, which might be inconvenient and time-consuming. For this reason, a video annotation platform has been developed in order to provide users more convenient and more interactive ways with video content. In the future of smart TV environment, users can follow annotated information, for example, a link to a vendor to buy the product of interest. It is even better to enable users to search for information by directly discussing with friends. Users can effectively get useful and relevant information about the product from friends who share common interests or might have experienced it before, which is more reliable than the results from search engines. Social networking services provide an appropriate environment for people to share products so that they can show new things to their friends and to share their personal experiences on any specific product. Meanwhile, they can also absorb the most relevant information about the product that they are interested in by either comments or discussion amongst friends. However, within a very huge graph of friends, determining the most appropriate persons to ask for information about a specific product has still a limitation within the existing conventional approach. Once users want to share or discuss a product, they simply share it to all friends as new feeds. This means a newly posted article is blindly spread to all friends without considering their background interests or knowledge. In this way, the number of responses back will be huge. Users cannot easily absorb the relevant and useful responses from friends, since they are from various fields of interest and knowledge. In order to overcome this limitation, we propose a method to filter a user's friends for information search, which leverages semantic video annotation and social networking services. Our method filters and brings out who can give user useful information about a specific product. By examining the existing Facebook information regarding users and their social graph, we construct a user profile of product interest. With user's permission and authentication, user's particular activities are enriched with the domain-specific ontology such as GoodRelations and BestBuy Data sources. Besides, we assume that the object in the video is already annotated using Linked Data. Thus, the detail information of the product that user would like to ask for more information is retrieved via product URI. Our system calculates the similarities among them in order to identify the most suitable friends for seeking information about the mentioned product. The system filters a user's friends according to their score which tells the order of whom can highly likely give the user useful information about a specific product of interest. We have conducted an experiment with a group of respondents in order to verify and evaluate our system. First, the user profile accuracy evaluation is conducted to demonstrate how much our system constructed user profile of product interest represents user's interest correctly. Then, the evaluation on filtering method is made by inspecting the ranked results with human judgment. The results show that our method works effectively and efficiently in filtering. Our system fulfills user needs by supporting user to select appropriate friends for seeking useful information about a specific product that user is curious about. As a result, it helps to influence and convince user in purchase decisions.

• Journal of Science Education
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• v.35 no.1
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• pp.1-12
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• 2011

The purpose of this study was to examine the effects of science class using the multimedia materials on high school students' attitude toward science. The subjects were 222 high school students. For this study, 11th graders at a high school were assigned to a comparison group and an experimental group. The experimental group was received science class using multimedia materials for 3 months. The research design was pretest-posttest control group design, the data were analyzed using PASW statistics 18.0 program. The types of multimedia materials used in experimental group were science fiction movies, science documentaries, TV programs, and Power Point presentations created by students. Before and after treatment, the attitude toward science tests were administered. Pre-tests and post-test score differences between 2 groups were analyzed by ANCOVA. The differences of attitude toward science based on gender were compared by analysis of covariance. And the perception on science class with multimedia materials were also investigated. The results of this study were as follows: First, the attitude toward science was improved significantly after applying science classes using multimedia materials. Especially, there were significant difference between pre-test and post-test in the score of attitude toward science class and attitude toward science content which were sub-area of attitude toward science. Second, there was no significant difference between female and male students in total score of attitude toward science. However, the attitude toward science, scientists and society, which was a sub-area of attitude toward science, female students scored significantly higher than male students. Third, 84% student showed a positive perception that the science class enhanced their interest in science. 69% the students responded that we had thought about Science-Technology-Society. Multimedia material types which the students prefered were science fiction movie, science documentaries, science TV programs, respectively.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.119-133
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• 2020

Recently, as famous YouTubers produce and broadcast videos that receive sponsorship and advertising such as indirect advertising (PPL), a so-called 'back advertising' controversy continues, and not only famous YouTubers but also entertainers are caught up in the issue. It is causing confusion among the public in Korea. This study attempts to find out the public's reaction before and after the controversy of 'back advertising' by YouTubers through comment analysis. Specifically, among text analysis using R programs, we intend to analyze the issue through various methods such as word cloud, qgraph analysis, LDA, and word2vec analysis, a deep learning technique. The target of the analysis was to analyze the channels of three YouTubers who belonged to the controversy of the 'back advertising' YouTuber and uploaded the 'Apology video'. The 5 most recent videos of Muk-bang YouTuber Moon Bok-hee, who has a similar content disposition to SussTV's Han Hye-yeon stylist, which was controversial, and Yang Pang, a YouTuber who showed various contents (August 09, 2020) Criterion and her first 5 videos uploaded were reviewed. As a result of the study, most of the comments that showed positive reactions before the controversy, but after the controversy, it was found that negative reactions accounted for most of the comments. Therefore, this study examines the degree of change of the public about influencers through comments after the controversy over 'back advertising' through various analysis using R program. This research also devises various measures to prevent the occurrence of back advertising of influencers in the future.