• 한국IT서비스학회지
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• 제15권1호
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• pp.97-111
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• 2016

In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

• Asia Marketing Journal
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• 제20권4호
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• pp.65-94
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• 2019

The purpose of this study was to analyze the brand loyalty formation by positive labeling. Affecting such factors as involvement, self-image, community engagement, preference, and choice cutback, positive labeling can be seen as one of psychological factors that shapes consumer's behavior and their decision. This study was carried out because little research was done to examine the influence of positive labeling toward brand loyalty, and also to find out the benefits that consumers can get from being labeled in positive terms. Data were collected through survey questionnaire and 151 usable responses were used. Following a series of pretests and confirmatory factor analysis helped to purify measures and verify the psychometric properties of the scale. Structural equation modeling with AMOS was used for testing of research hypotheses. The result of data analysis demonstrated the positive relationship between labeling and brand loyalty, i.e. positive labeling indirectly leads to consumers' loyalty toward a brand. Findings revealed significant relationship between involvement and emotional attachment, as well as the relationship between community engagement and choice cutback. The results gave support for the hypothesis of moderating effect of buzz on the relationship between involvement and emotional attachment, even though the hypothesis of moderating effect of distinction was rejected. Taking Apple's rivalry strategy as initial point, this study highlights the role of labeling in creating social identity. The study attempts to show the positive consequences of labeling strategy for firms that seeks ways of good competition without engaging into conflicts.

• 디지털콘텐츠학회 논문지
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• 제17권1호
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• pp.1-10
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• 2016

1인 미디어 방송을 지상파방송으로 확장한 새로운 포맷의 "마이리틀 텔레비전"이 많은 화제성지수를 만들어내고 있다. 2015년 4월 첫 방송을 시작해서 동일 시간대 시청률 1위를 지속하고 있다. 시청자가 다음 TV팟을 통해서 프로그램에 직접 참여해 실시간으로 시청자와 진행자가 소통을 하면서 다양한 의견을 프로그램에 반영하고 있다. SNS를 통해서 프로그램에 대한 많은 정보가 확산되면서 프로그램 시청률 상승으로 이어지고 있다. 최근에는 시청률로만 프로그램을 평가했던 부분에서 SNS를 통한 빅데이터 분석을 통해서 프로그램에 대한 화제성지수를 발표하고 있다. 프로그램 시청률과 버즈량과의 상관관계에 대한 연구가 늘어나고 있다. 본 연구에서는 버즈량보다 확대된 개념의 화제성지수가 시청률에 어떠한 영향을 미치는지 분석하였다. 연구결과 화제성지수는 시청률에 정의(+) 영향을 미친 것으로 분석되었다. 방송 프로그램에 대한 SNS의 빅데이터 연구에 많은 도움이 될 것이다.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.65-72
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• 2023

Cloud Computing is one of the current research areas in computer science. Recently, Cloud is the buzz word used everywhere in IT industries; It introduced the notion of 'pay as you use' and revolutionized developments in IT. The rapid growth of modernized cloud computing leads to 24×7 accessing of e-resources from anywhere at any time. It offers storage as a service where users' data can be stored on a cloud which is managed by a third party who is called Cloud Service Provider (CSP). Since users' data are managed by a third party, it must be encrypted ensuring confidentiality and privacy of the data. There are different types of cryptographic algorithms used for cloud security; in this article, the algorithms and their security measures are discussed.

• Asia pacific journal of information systems
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• 제26권1호
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• pp.124-142
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• 2016

Companies operating in social network platforms continue to improve and expand their marketing techniques. This study examines the practice of "gating", which involves virtual barriers between social network users and company content. Gates demand mandatory user endorsements, in the form of a Facebook "Likes", Twitter "retweets" etc., to gain access to company content, such as coupons and rewards,. Gating practices demand a mandatory endorsement before any content consumption takes place. Thus, while user endorsements are assumed to arise voluntarily from trusted known sources, gating practices would appear to violate this assumption. However, whether this violation lessens the effectiveness of gating practices still requires empirical validation. We investigate this question through the use of a unique panel data set that includes data on "like" endorsements obtained from a number of real-world Facebook business pages. Results of the study show that gating practices are effective for endorsement solicitation; however, gates may interfere with more traditional marketing activities.

• Journal of the Korean Data and Information Science Society
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• 제26권5호
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• pp.1087-1095
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• 2015

인플루엔자는 흔히 독감으로 불리는 질병으로 인플루엔자 바이러스가 호흡기 (코, 인후, 기관지, 폐 등)에 감염되어 생기는 병이다. 감기와는 달리 심한 증상을 나타내거나 생명이 위험한 합병증 (폐렴 등)을 유발할 수도 있다. 본 연구에서는 인플루엔자에 대한 예측모형을 다루었으며, 주로 회귀적인 모형을 고려하였다. 기존의 연구들이 주로 기상요인을 예측변수로 사용한 반면, 본 연구에서는 소셜요인의 효과를 살펴보았으며 그 결과 기상요인과 대등한 설명력을 가짐을 확인하였다. 반응변수로는 국민건강보험공단에서 제공하는 인플루엔자 진료건수가 사용되었고, 설명변수에는 기상청에서 제공하는 기상정보와 트위터에서의 인플루엔자 연관키워드 빈도가 사용되었다. 모형의 비교를 위해 시계열 모형도 함께 제시되었다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2013년도 춘계학술발표대회
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• pp.610-613
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• 2013

Vehicular Ad Hoc NETwork (VANET), a subclass of Mobile Ah Hoc NETwork (MANET) has been a tech-buzz for the last couple of decades. VANET, yet not deployed, promises the ease, comfort, and safety to both drivers and passengers once deployed. The by far most important factor in successful VANET application is the data dissemination scheme. Such data includes scheduled beacons that contain whereabouts information of vehicles. In this paper, we aim at regularly broadcasted beacons and devise an algorithm to disseminate the beacon information up to a maximum distance and alleviate the broadcast storm problem at the same time. According to the proposed scheme, a vehicle before re-broadcasting a beacon, takes into account the current vehicular density in its neighborhood. The re-broadcasters are chosen away from the source of the beacon and among the candidate re-broadcasters, if the density in the neighborhood is high, then the candidate rebroadcaster re-broadcasts the beacon with high probability and with low probability, otherwise. We also performed thorough simulations of our algorithms and the results are sound according to the expectations.

• Journal of Sport and Applied Science
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• 제8권1호
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• pp.11-17
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• 2024

Purpose: The purpose of the study was to understand a trend of esports in terms of gamers' and fans' perceptions toward esports using social big data. Research design, data, and methodology: In this study, researchers first selected keywords related to esports. Then a total of 10,138 buzz data created at twitter, Facebook, news media, blogs, café and community between November 10, 2022 and November 19, 2023 were collected and analyzed with 'Textom', a big data solution. Results: The results of this study were as follows. Firstly, the news data's main articles were about competitions hosted by local governments and policies to revitalize the gaming industry. Secondly, As a result of esports analysis using Textom, there was a lot of interest in the adoption of the Hangzhou Asian Games as an official event and various esports competitions. As a result of the sentiment analysis, the positive content was related to the development potential of the esports industry, and the negative content was a discussion about the fundamental problem of whether esports is truly a sport. Thirdly, As a result of analyzing social big data on esports and the Olympics, there was hope that it would be adopted as an official event in the Olympics due to its adoption as an official event in the Hangzhou Asian Games. Conclusions: There was a positive opinion that the adoption of esports as an official Olympic event had positive content that could improve the quality of the game, and a negative opinion that games with actions that violate the Olympic spirit, such as murder and assault, should not be adopted as an official Olympic event. Further implications were discussed.

• 한국빅데이터학회지
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• 제2권2호
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• pp.57-66
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• 2017

프랜차이즈 경쟁의 심화에 따라 기업은 프로모션에 상당한 재원을 투자하고 있으며, 이에 프로모션의 효과 측정의 필요성이 증가하고 있다. 본 연구는 프랜차이즈 외식 산업에서 이러한 프로모션의 효과를 조사하기 위해 대표적 소셜 네트워크 서비스인 트위터 데이터를 경험적으로 분석하였다. 먼저 프로모션의 간격과 기간, 그리고 계절이 프로모션의 효과에 영향을 미치는 요인임을 통계적으로 입증했고, 나아가 각 요인별로 프로모션의 효과에 영향을 미치는 배경을 파악하여 외식 산업 내 기업의 업종에 따른 프로모션 전략을 제안하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권10호
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• pp.4204-4222
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• 2015

Cloud is the latest buzz word in the internet community among developers, consumers and security researchers. There have been many attacks on the cloud in the recent past where the services got interrupted and consumer privacy has been compromised. Denial of Service (DoS) attacks effect the service availability to the genuine user. Customers are paying to use the cloud, so enhancing the availability of services is a paramount task for the service provider. In the presence of DoS attacks, the availability is reduced drastically. Such attacks must be detected and prevented as early as possible and the power of computational approaches can be used to do so. In the literature, machine learning techniques have been used to detect the presence of attacks. In this paper, a novel approach is proposed, where intelligent rule based feature selection and classification are performed for DoS attack detection in the cloud. The performance of the proposed system has been evaluated on an experimental cloud set up with real time DoS tools. It was observed that the proposed system achieved an accuracy of 98.46% on the experimental data for 10,000 instances with 10 fold cross-validation. By using this methodology, the service providers will be able to provide a more secure cloud environment to the customers.