• Cartoon and Animation Studies
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• s.44
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• pp.285-306
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• 2016

With the increase use of smartphones, users can consume contents such as webtoon, webnovel and TV drama directly provided by the producers. In this Direct-to-Consumer era, webdrama services from the portal websites are increasing rapidly. Webdramas such as , , and can be analyzed in real time using responses such as unique users, likes, and comments. The analyses used in this research were Social Media Big Data Mining Method and Opinion Mining Method. Specific key words from webdrama can be extracted and viewers positive, neutral or negative emotion can be predicted from the words. The analyses of popular webdramas showed that the established K-Pop Idol member appearance and servicing portal site greatly influence the views, traffics, comments, and likes. Also, 'Mobile TV' proved the effectiveness as another platform other than television. Mobile targeted contents and robust business models still to be developed and identified. Overcoming these few tasks, Korea will be proven to be a webdrama content powerhouse.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.37-48
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• 2022

With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.535-542
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• 2023

This study attempted to identify various variables that affect satisfaction and continued use intention of the subscription economy services. Through previous research studies, individual characteristics and service characteristic variables were considered together. Finally, use motivation, platform characteristic factors, and product and service characteristic factors were classified and examined. As a result of the study, the motive for using the service that affects the satisfaction of the subscription economy service was found to be functional hedonic, and economic motive, and platform recency and convenience, economic utility, and perceived personalization had a positive effect. Functional and hedonic motives and convenience showed positive influences on continued use intention, while social motives showed negative influences. In addition, it was confirmed that economic motivation, platform recency, economic utility, and perceived personalization showed a positive influence on the intention to continued use intention by mediating satisfaction with subscription economy services.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.125-132
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• 2021

This study deals with the influencing factors on flow and addiction perceived by users of Tiktok service, an SFV service platform that is expanding the market in the middle area between social media and OTT. As the number of Tiktok users increases, researchers thought that research on the cause of addiction would be necessary. Since media users lack media consumption time, they produce and share SFVs rather than long videos, and are affected by exogenous variables. In addition, attachment is divided into interpersonal relationships and attachment to services, and the path of attachment was confirmed to be connected to flow and addiction. Through this study, the researchers considered that there were theoretical and practical contributions in that the path leading to addiction of video media services was set and verified as self-exposure and attachment, flow and addiction. These research results can be applied to more diversified video-centered media services, and can be expected to be used for new media emerging in the future.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.67-101
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• 2014

The use of new technology greatly shapes the marketing strategies used by companies to engage their consumers. Among these new technologies, social media is used to reach out to the organization's audience online. One of the most popular social media channels to date is the microblogging platform Twitter. With 500 million tweets sent on average daily, the microblogging platform is definitely a rich source of data for researchers, and a lucrative marketing medium for companies. Nonetheless, one of the challenges for companies in developing an effective Twitter campaign is the limited theoretical and empirical evidence on the proper organizational usage of Twitter despite its potential advantages for a firm's external communications. The current study aims to provide empirical evidence on how firms can utilize Twitter effectively in their marketing communications using the association between brand personality and brand engagement that several branding researchers propose. The study extends Aaker's previous empirical work on brand personality by applying the Brand Personality Scale to explore whether Twitter brand communities convey distinctive brand personalities online and its influence on the communities' level or intensity of consumer engagement and sentiment quality. Moreover, the moderating effect of the product involvement construct in consumer engagement is also measured. By collecting data for a period of eight weeks using the publicly available Twitter application programming interface (API) from 23 accounts of Twitter-verified business-to-consumer (B2C) brands, we analyze the validity of the paper's hypothesis by using computerized content analysis and opinion mining. The study is the first to compare Twitter marketing across organizations using the brand personality concept. It demonstrates a potential basis for Twitter strategies and discusses the benefits of these strategies, thus providing a framework of analysis for Twitter practice and strategic direction for companies developing their use of Twitter to communicate with their followers on this social media platform. This study has four specific research objectives. The first objective is to examine the applicability of brand personality dimensions used in marketing research to online brand communities on Twitter. The second is to establish a connection between the congruence of offline and online brand personalities in building a successful social media brand community. Third, we test the moderating effect of product involvement in the effect of brand personality on brand community engagement. Lastly, we investigate the sentiment quality of consumer messages to the firms that succeed in communicating their brands' personalities on Twitter.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.144-147
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• 2010

Recently the change of content consumption trend activated the social video sharing platform and the video clip itself. There have been intensive interests and efforts to automatically abstract compact and meaningful video clips. In this paper, we propose a method which use the clustering of the bookmark data created by collective intelligence instead of using the video content analysis. The partitional clustering of points in 2-dimensional space derived from the bookmark data make it possible to abstract highlights effectively. The method is enhanced by the 1-dimensional accumulated bookmark count graph. Experiments on the real data from KBS internet service show the effectiveness of the proposed method.

• Journal of Information Science Theory and Practice
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• v.10 no.2
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• pp.17-29
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• 2022

Facebook is very popular among young people and especially university students. Therefore, Facebook is the most logical platform to be used by academic libraries for promotional purposes and reaching out to user communities. This study aims to measure the effectiveness of using Facebook in connecting with students in academic libraries. A questionnaire survey was conducted to collect research data from students at four Vietnamese universities. A total of 1,670 valid questionnaires were returned, and more than half of the respondents were females between the ages of 18 and 22 years. The survey results found that libraries' Facebook pages did not receive adequate attention and interaction from students. Besides that, the information needs of students and social media content in general affected student acceptance of libraries' Facebook pages. These factors are demonstrated by the great majority of students who used Facebook often for various purposes, but fewer accessed library pages and they were not actively engaged in library posts. Students were interested in the information they already tended to get from libraries and were optimistic about the quality of library posts. However, they still expected more diverse and attractive content from the libraries. The findings of this study can help libraries create a close connection with students by satisfying their needs and expectations on Facebook.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.1-31
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• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1111-1117
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• 2023

Recently, South Korean newspapers began trying to charge for online news. This study attempts to shed light on the factors that influence payment for online news by analyzing Korea Press Foundation's 2022 Media Audience Survey (N = 58,936). The results of this study showed a steady increase in past payment and paying intent for online news since 2020. Predictors of past payment for online news included gender, age, and education, and interest in political and social issues. News use through specific media (i.e., newspapers, magazines, portals, messengers, social media, video sites, and podcasts), as well as mobile applications and e-mail newsletters, were found to contribute to paid subscriptions. Based on the findings of the study, news organizations should prepare to offer differentiated news content through their own news platforms and establish concrete plans to build trust in news.