• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.138-147
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• 2018

The network analysis is done to explore what kind if issues are diffused about earthquake and the role of social media. The types of disaster information is classified into formal and informal. The role of actor is classified based on the concentrativeness and the diffusion of issue. Youttube is functioned as a formal channel and an informal channel when disaster happened. In case of government's video, issue contractiveness is high but the diffusion is low. In case of media's video, issue contractiveness and the diffusion are all high. In case of individual channel, issue contractiveness is low, but diffusion is high. In disaster, youtube is a tool to respread the disaster issue. Government needs to try diffusion of government's news actively in disaster.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.121-131
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• 2022

We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

• Journal of the Korean Society of Clothing and Textiles
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• v.37 no.2
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• pp.186-201
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• 2013

This study investigates the effects of information type, direction of information, method of suggestion, tie strength, and interactions among these variables on the acceptance and diffusion of fashion product information in the mobile Facebook environment. Two subsequent studies were conducted to test the relationships among mobile SNS WOM factors. Two independent on-line surveys were implemented. Six hundred forty consumers aged between 20 and 39 were recruited for Study 1, and four hundred and eighty for Study 2. We manipulated the WOM delivery situation by information type (factual/evaluative), information directionality (positive/negative), tie-strength (strong/weak), and information presentation method (text/image/rink). Eight scenarios were developed and randomly assigned to the research participants. Frequency analysis, reliability, factor analysis, regression analysis, and ANOVA were implemented using SPSS 18.0. The Analysis of experiment data produced interesting results. Most WOM factors (including the information type, information presentation method, and tie strength) influence WOM acceptance; however, only the tie strength effected WOM activity. It was also proven that people are prone to accept information that is more realistic, objective, and negative, and they tend to accept information with visual factors, such as images and video clips rather than a simple text message. In this study, we offer a practical perspective to fashion industry and marketers who have an interest in SNS marketing. We have defined the distinct characteristics of mobile WOM that have been formed by a combination of former on/off-line WOM characteristics. To examine the moderating roles of two types of consumer innovativeness, fashion innovativeness and technology innovativeness were also measured and found to have significant moderating effects between mobile SNS WOM factors and their consequences. The paper concludes with a discussion on managerial implications and limitations.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.399-407
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• 2018

The influence of SNS platform in the mobile environment has grown greatly. Among the various social networking services(SNS), this study analyzed the question of 311 women to investigate whether any difference exists between reliability of contents information, informativeness and playfulness as well as how attributes of contents information influence user attitude depending on the difference in type of providing information provided by "Innisfree" Cosmetics, the company account of Instagram. According to analysis, first, no difference exists between reliability of contents information, informativeness and playfulness depending on the type of providing information. Second, reliability and the playfulness of contents information influence purchase intention. Third, contents information "informativeness" and "playfulness" influence loyalty. Fourth, the "informativeness" and "playfulness" of contents information influence User Satisfaction. Considering such result, it is confirmed that the type of providing information provided by company does not influence account attributes and the "playfulness" of contents information is significant factor which influences all user attitude.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3777-3785
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• 2013

This study aimed to find out adolescents' media literacy in terms of reading, writing, and enjoying media or messages. For the purpose, we analyzed the data garnered from 1,036 students enrolled in 5 middle and 5 high schools, respectively. The analyses of the data are summarized as follows: First, mobile phone was most widely used among others, followed by TV, the Internet, mp3 player, computer or video game, radio, a video or DVD in the order. Second, a gender effect was significant in terms of the variety of activities with the Internet, mobile, and SNS: boys were more active in the use of the Internet while girls carried out more activities with a mobile phone and SNS media. Third, high school students showed more critical attitude towards information on the Website than did the middle school students. Fourth, Girls than boys, and high schoolers than middle schoolers, tended to be more active in the production of contents, self-expression, as well as participating in social and political issues online. Fifth, for the enjoyment experiences, time spent for games took up the most of the students' leisure activities, followed by watching TV and the use of the Internet. The findings of the study were discussed in light of media convergence, with implications for developing media literacy education for the youth.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.359-372
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• 2022

This study aimed to derive a YouTube content strategy that can be exposed to Trending for a long time by comparing the features of 20 channels in the short/long term using 'YouTube Trending' data in 2021. First, through Pearson's correlation analysis, we found that various factors such as 'the number of title or tag letters' related to long-term exposure, and set this as an index to compare features. As a result, 1)'video title' of about 40-45 letters without excessive special characters, 2)'video length' within 10 minutes, 3)'Video description' is effective when writing 2-3 sentences and adding SNS information or including 3 key tags. Also, it would be more effective if you set key tag pairs such as (먹방, mukbang), (역대급, 레전드) derived through text mining. Through this, the channel will spread globally, bringing various advantages, and will be used as an indicator to evaluate the globality of the channel.

• The Journal of Information Systems
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• v.32 no.2
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• pp.177-190
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• 2023

Purpose Recently, as a new business marketing tool, short form content focused on fun and interest has been shared as hashtags. By extracting positive and negative keywords from media audiences through comment analysis of social media news, various stakeholders aim to quickly and easily grasp users' opinions on major news. Design/methodology/approach YouTube videos were searched using the YouTube Data API and the results were collected. Video comments were crawled and implemented as HTML elements, and the collection results were checked on the web page. The collected data consisted of video thumbnails, titles, contents, and comments. Comments were word tokenized with the R program, comparing positive and negative dictionaries, and then quantifying polarity. In addition, social network analysis was conducted using divided positive and negative comments, and the results of centrality analysis and visualization were confirmed. Findings Social media users' opinions on issue news were confirmed by analyzing and visualizing the centrality of keywords through social network analysis by dividing comments into positive and negative. As a result of the analysis, it was found that negative objective reviews had the highest effect on information usefulness. In this way, previous studies have been reaffirmed that online negative information has a strong effect on personal decision-making. Corporate marketers will analyze user comments on social network services (SNS) to detect negative opinions about products or corporate images, which will serve as an opportunity to satisfy customers' needs.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.25-32
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• 2016

The current research was to investigate the effects of discussion activities based on Havruta style on elementary school students' social studies communication skills. For this purpose, we examined a comparative study between 5th grade students and other students of partner schools. As research results, first, online classes using video conference equipment and smart devices will enhance the students' interest and participation in class. Second, the Havruta style helps students not only acquire and internalize knowledge by themselves through the course of reciprocal questions and discussions but also improve presentations and participations. Third, it is necessary not only to draft a new lesson plan and to reconstruct the education process for video and online classes but also to develop the classes with a lesson plan after preparations and discussions with colleague teachers; the process of reflection, such as writing a lesson research journal, has a positive effect to improve the quality of cooperative classes. Fourth, using SNS discussion activities to serve as a complementary activity is good, and two teachers can evaluate each of the students' achievement. It is necessary to have a sufficient number of schools where video and online cooperative learning is possible with video equipment provided. To maximize the effect of video and online classes, various studies and teacher trainings are needed. Education office needs to provide a server that enables students in small and large classes to freely engage in cooperative learning.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.127-134
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• 2022

Steganography is a hidden technique in which secret messages are hidden in various multimedia files, and it is widely exploited for cyber crime and attacks because it is very difficult for third parties other than senders and receivers to identify the presence of hidden information in communication messages. Botnet typically consists of botmasters, bots, and C&C (Command & Control) servers, and is a botmasters-controlled network with various structures such as centralized, distributed (P2P), and hybrid. Recently, in order to enhance the concealment of botnets, research on Stego Botnet, which uses SNS platforms instead of C&C servers and performs C&C communication by applying steganography techniques, has been actively conducted, but image or video media-oriented stego botnet techniques have been studied. On the other hand, audio files such as various sound sources and recording files are also actively shared on SNS, so research on stego botnet based on audio steganography is needed. Therefore, in this study, we present the results of comparative analysis on hidden capacity by file type and tool through experiments, using a stego botnet that performs C&C hidden communication using audio files as a cover medium in Telegram Messenger.