• 한국벤처창업학회:학술대회논문집
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• 2021.04a
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• pp.125-130
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• 2021

코로나19 팬데믹은 삶의 많은 부분을 변화시켰다. 국가 간 통제 및 사회적 거리두기로 인한 직접적인 만남이 제한되고, 우리 생활의 많은 영역이 비대면으로 전환되었다. 이런 상황에서 의사소통 및 사회적, 경제적 교류를 위한 대안으로 레거시 미디어콘텐츠의 퇴조와 함께 소셜미디어 등의 뉴미디어 콘텐츠를 활용한 경제활동이 이루어지고 있다. 미디어콘텐츠를 기반한 경제 생태계는 복잡해지고 있으며, 플랫폼 간 경쟁 또한 매우 치열해지는 상황이다. 급속하게 변하고 있는 디지털 환경의 사회 구조는 경제 전반에 큰 영향을 주고 있으며, 경제활동을 지속하려는 개인과 정책지원을 하는 국가에도 중요한 현안이 되어 있다. 고령화 사회로의 빠른 진입으로 인적 자본의 활용 문제가 대두되고, 코로나19로 인한 경제불황이 대면 경제활동을 크게 위축시키면서 고용 감소와 불안정성이 대두되었다. 그에 따라 비대면 산업이 활성화되고, 플랫폼 산업 등 미디어콘텐츠 기반의 새로운 경제활동이 주목받고 일상화되었다. 또한 미디어콘텐츠 기반 비즈니스에 실효성 있는 인적 자본 활용이 국가의 주요 정책이 되었다. 따라서 본 연구는 미디어콘텐츠 활용과 신 정보화 도구를 활용한 디지털 역량이 경제활동 지속 의도에 어떤 영향을 미치는지에 대하여 실증적으로 분석하고 검증하여 실무적 시사점을 제시하고자 한다.

• 한국벤처창업학회:학술대회논문집
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• 2021.04a
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• pp.61-65
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• 2021

세계적으로 창업 생태계가 구축되면서 기술창업 분야가 두각을 보이고 있다. 기술창업은 기술력을 통한 지속력뿐 아니라 혁신적으로 변화를 진행시키므로 기술에 대한 투자 동향을 날이갈수록 높아지고 있다. 하지만 기술이 발전하면서 함께 주목되고 있는 분야가 사회적 가치를 가지고 있는 소셜벤처이다. 특히 UN에서 발표한 지속가능한 발전목표(SDGs)의 경우 필수적으로 사업 비즈니스 모델적으로 채택된 분야를 갖고 있어야하며 비재무적성과를 판단하는 기준인 ESG 또한 필수적인 사회적 가치 요소로 떠오르고 있다. 이러한 흐름 속에서 기술 역량을 내세웠을 때와 사회적 가치를 내세웠을 때 투자자들은 어떤 역량과 특성을 더 선호하며 투자 유무가 결정되는지를 분석해보고자 한다. 결국 기술 역량 또는 사회적 가치 둘중 하나를 내세운다는 것은 기업의 이미지를 나타내는것과 같은 의미이다. 이에 기술역량과 사회적 가치가 기업이미지를 유능 또는 따뜻함 중 어떻게 나타나는지 알아보고 투자 유무에 미치는 영향을 보고자 한다. 본 연구에서는 기술창업 기업 기술 범위를 인공지능(AI), 빅데이터, 사물인터넷(IoT), 바이오(Bio)로 총 4개로 분류하였다. 기술 창업의 기술범위를 독립변수로 설정하였으며 기술창업에서 기술역량 또는 사회적 특성을 내세웠을 때 기업이미지가 유능하게 보여지는지 따뜻하게 보여지는지를 알아보고자 한다. 기업이미지가 유능함 또는 따뜻함으로 비춰졌을 때 벤처투자에서 투자 유무가 결정되는지를 검증하고자 한다. 검증 방법에서는 벤처투자자가 아닌 창업교육을 이수하는 대학생들을 대상으로 모의투자를 통해 연구를 진행하고자 한다.

• Management & Information Systems Review
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• v.34 no.1
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• pp.1-20
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• 2015

This study analyses the relationship with the feature of the web usability and Social commerce. Therefore, this research tries to investigate the relationship about in which the characteristic of the web-site usability is connected through the confidence about the Social commerce site to the re-purchase. The existing research that the information system and Electronic commerce relates is considered and the usability factor about the Social commerce site tries to be drawn and these try to verify on the relationship with the trust building of the user about the Social commerce site and purchasing intention through the positive research. The result is follows. First, the visual property of the Social commerce site was confirmed to have the descriptive ability noted to the confidence. Second, it was confirmed to have the descriptive ability that information characteristic about the Social commerce site notes to the confidence. Third, it was confirmed to have the descriptive ability that relative characteristic about the Social commerce site notes to the confidence. The importance of the web-site usuability has preferentially to be considered in being put through this research and building the confidence of the social commerce user could be known. When running with the social commerce site design, this is determined because it can become the useful standard.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.61-76
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• 2018

Everything is coming into the world of network where modern people are living. The Internet of Things that attach sensors to objects allows real-time data transfer to and from the network. Mobile devices, essential for modern humans, play an important role in keeping all traces of everyday life in real time. Through the social network services, information acquisition activities and communication activities are left in a huge network in real time. From the business point of view, customer needs analysis begins with SNS data. In this research, we want to build an automatic collection system of SNS contents of web environment in real time using Python. We want to help customers' needs analysis through the typical data collection system of Instagram, Twitter, and YouTube, which has a large number of users worldwide. It is stored in database through the exploitation process and NLP process by using the virtual web browser in the Python web server environment. According to the results of this study, we want to conduct service through the site, the desired data is automatically collected by the search function and the netizen's response can be confirmed in real time. Through time series data analysis. Also, since the search was performed within 5 seconds of the execution result, the advantage of the proposed algorithm is confirmed.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.197-216
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• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.663-669
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• 2016

This study explores the effect of tagging in Social Network Services, especially Facebook, which has become popular as a marketing platform. In Facebook, users generally make recommendations using 'Like', 'Share', or 'Tag'. 'Tag' is different from 'Like' or 'Share' in that it can be used to deliver certain messages directly to specific people based on their interests or characteristics. Tagging can be categorized into rewarded tagging and non-rewarded tagging. As a result of our exploratory research, we found that non-rewarded tagging by certain users can indicate that the people, who are tagged, are interested in the contents of the users and share the same interest as them. Also, tagging indicates that these users want to share these services, such as restaurants and tours, with their friends who are tagged in the contents. Therefore, this study sheds light on the importance of the tagging function, as well as 'Like' and 'Share'.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.455-461
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• 2012

The paper explores the relationship among paradigms, ecosystem which need to establish broadcasting, information and communications industry as the core of national competitiveness in the digital convergence era, and proposes the future progressing strategies and policies directions that consider environmental factors which all mass media converged on Internet. This paper makes an attempt to contribute innovative & integrated perspectives in the industry.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.90-102
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• 2013

K-POP has become a part of killer contents attracting worldwide attention beyond Asia. The purpose of this study aims to identify some critical factors for recent success of K-POP. In order to do that, the influence of the change in media on the globalization of popular culture was explored and its required conditions were analyzed. And the international and domestic contents production cases were investigated and the possibility of expansion of Korean Wave through reproduction of diverse contents was discussed. The potential markets for further development of Korean Wave were also analyzed and gave some suggestions for building new businesses model and effective infrastructure of among producer of contents, platform subscriber, network provider, terminal enterprise and retailers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.5
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• pp.831-847
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• 2013

The various types of data are being created in large quantities resulting from the spread of social media and the mobile popularization. Many companies want to obtain valuable business information through the analysis of these large data. As a result, it is a trend to integrate the big data technologies into the company work. Especially, Hadoop is regarded as the most representative big data technology due to its terabytes of storage capacity, inexpensive construction cost, and fast data processing speed. However, the authentication token system of Hadoop Distributed File System(HDFS) for the user authentication is currently vulnerable to the replay attack and the datanode hacking attack. This can cause that the company secrets or the personal information of customers on HDFS are exposed. In this paper, we analyze the possible security threats to HDFS when tokens or datanodes are exposed to the attackers. Finally, we propose the secure authentication protocol in HDFS based on hash chain.

• Journal of Korea Multimedia Society
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• v.16 no.5
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• pp.657-666
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• 2013

Today, many aspects of our lives are characterized by the rapid influx of large amounts of data from various application domains. The applications that produce this massive of data span a large spectrum, from social media to business intelligence or biology. This massive influx of data necessitates large scale parallelism for efficiently supporting a large class of analysis tasks. Recently, there have been extensive studies in using MapReduce framework to support large parallelism. While this technique has produced impressive results in diverse applications, the same can not be said for multimedia applications where most of users are interested in a small number of results having high or low score. Thus, in this paper, we develop the data partitioning algorithm which is able to efficiently process large data set having different data utility. The experiment results show that the proposed technique provides significant execution time gains over the existing solution.