• Review of KIISC
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• v.22 no.8
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• pp.61-73
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• 2012

인프라스트럭처 상용 클라우드 서비스(IaaS)의 이용 시 클라우드 기반의 네트워크에 어떤 정보보호기술을 적용할 지에 대한 고려를 하는 것은 기존의 네트워크에 정보보호기술을 적용하는 것과 차이가 있다. 그 차이점은 클라우드 서비스 사업자가 서비스 형태로 제공하는 정보보호 기술들을 선택하여 적용할 수 밖에 없다는 것이다. 본 연구는 사업자가 제공하는 정보보호 서비스들이 어떠한 것이 있는지를 분석 종합하고, 기술의 특성을 고려해 재분류하고, 기업별로 제공되는 정보보호기술의 적용에 드는 비용을 함께 조사하여 각 사업자들의 정보보호기술의 과금 형태를 분석하였다. 또한, 이러한 분석을 기반으로 게임, 의료 및 소셜 커뮤니티 사이트 등의 기업 유형별 필요 기술을 선택하는 시나리오 분석을 시도 하였다. 본 연구의 기여점은 클라우드 환경에서의 정보보호 기술의 분석을 통해 해당 기술을 적용하고자 하는 사람들이 어떻게 기술을 선택 및 적용 할지에 대한 실질적인 방법을 제시한 것에 있다.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.560-569
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• 2015

Crowd funding is the method of raising money for a project, companies from a large group of people via the Internet, in return for future products or equity. Kickstarter is the largest and most successful crowdfunding site where creative projects raise reward based funding. Drawing on dataset of 80,267 projects with combined funding over $1.3b from 8.1m people, this paper suggest that backer select project based on their preference on the project, instead profitability of the project. It suggests that well-established platform and big size of network increases the chance of success of the project due to a ripple effect and blockbuster effects. Clear communication about the project's idea and goal is highly correlated with success. Regular communication on the project site, such as by constant progress updates, helps the success of the project. Equity-based crowdfunding is emerging as an innovative means of raising capital for businesses, so it has been receiving a lot of attention and expectation from the government and the market. The findings of this paper and others will help to get some understanding and insight into equity-based crowdfunding. However, Kickstarter differs from equity-based crowdfunding in the goals of the backers. Kickstarter's backers are not investors, they are contributors. To understand equity-based crowdfunding, the subject will need further study.

• 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.

• Korean journal of communication and information
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• v.66
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• pp.59-86
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• 2014

This study explored how rumor is diffused via Twitter and how the characteristics of rumor affect the interactivity among users in the Korea-U.S. FTA case. A key word search located three issues as major ones related to the Korea-U.S. FTA: appendectomy myth, collapse of health insurance, and increases in medicine prices. The arousal of rumor has two dimensions: fact and expression. The fact arousal was the highest in the issue of 'appendectomy myth', and the expression arousal the highest in 'increases in medicine prices'. The rumor diffusion took the 'explosive wave' in the issue of appendectomy myth, the 'latent wave' in the issue of increase in medicine prices, and the 'repetitive wave' in the issue of collapse of health insurance. Correlation analyses revealed a high correlation between the arousal intensity of rumor and the user interactivity in the issue of collapse of health insurance. The study showed that Twitter took a role of diffusing negative messages about the Korea-U.S. FTA. Results implies that government officials and journalists pay attention to Twitter for sensing the public opinion when building policies and managing crises.

• Journal of the Korean Society for information Management
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• v.29 no.1
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• pp.375-393
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• 2012

The population aging occurs rapidly due to the advancement of the medical technology and living conditions and this led increased interests in how the elderly manages their lives. This study attempted to understand the information needs and behavior of the elderly users as well as to find about their information access and online communications. Based on the analysis of the interviews with thirty-two elderly users, they mainly looked for information on the topics such as health, news, leisure, and hobby. In addition, they primarily used television, radio, Internet, family members, relatives, and newspaper to obtain information. Their current use of social computing services including online communities, blogs, social network sites were low. However, the elderly users were aware of the social computing services' effectiveness in increasing the satisfaction and happiness of their lives by expanding the opportunities for them to communicate with family members and other social members.

• Journal of Information Technology and Architecture
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• v.9 no.3
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• pp.333-344
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• 2012

This paper proposes a system which recommends movies using information from social network services containing personal interest and taste. Method for establishing data is as follows. The system gathers movies' information from web sites and user's information from social network services such as Facebook and twitter. The data from social network services is categorized into six steps of emotion level for more accurate processing following users' emotional states. Gathered data will be established into vector space model which is ideal for analyzing and deducing the information with the system which is suggested in this paper. The existing similarity measurement method for movie recommendation is presentation of vector information about emotion level and similarity measuring method on the coordinates using Cosine measure. The deducing method suggested in this paper is two-phase arithmetic operation as follows. First, using general cosine measurement, the system establishes movies list. Second, using similarity measurement, system decides recommendable movie list by vector operation from the coordinates. After Comparative Experimental Study on the previous recommendation systems and new one, it turned out the new system from this study is more helpful than existing systems.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.257-274
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• 2014

Social Network Services (SNSs) have grown to be new and promising tools of marketing. By referring to researches done on e-mail viral marketing, this paper operationizes SNS viral marketing effectiveness to accurately reflect marketing success in SNS environment, and tries to identify its affecting factors. As potential affecting factors, fan size, advertisement type, existence of engagement elicitation and incentive are identified. By sampling real advertisement postings on Facebook, we showed that fan size, advertisement type, and engagement elicitation are factors affecting SNS viral marketing success. This research expanded the conventional model of viral marketing into SNS settings to improve understanding on SNS viral marketing. Motivation is discussed as an important factor, and this research showed that viral campaign can be more successful when it triggers internal motivation to engage, but not the external motivation. This research could also be a guide for practitioners on how to post a successful advertisement in SNSs.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.292-295
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• 2018

Open API의 사용이 대중화되면서 대형 포털사이트 및 대형 소셜 네트워크 서비스에 입력한 개인정보를 바탕으로 사용자들이 원하는 서비스를 제공하는 외부 서비스(Third-party application)의 수가 계속 증가하고 있다. 이러한 외부 서비스들이 정보 제공자에게 개인정보를 요청할 때, 외부 서비스가 권한 부여를 받은 정당한 요청을 하는지 여부를 확인하기 위해 OAuth 인증 프레임워크를 사용한다. 그러나 외부 서비스가 유효한 요청을 하고 있음을 판단하기 위해 사용하는 엑세스 토큰을 탈취하면 이를 이용하여 로그인 과정을 우회할 수 있으며, 개인정보 또한 쉽게 취득 가능하다. 본 논문에서는 이러한 취약점을 해결하기 위해 OAuth 인증 프레임워크에 2차적인 인증과정을 추가하여 엑세스 토큰의 탈취를 방지하여 사용자의 계정정보와 개인정보를 보호하는 프레임워크를 제시한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.467-468
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• 2021

본 논문에서는 자료수집(데이터 크롤링)을 이용해 많은 채용정보를 쉽게 접근할 수 있도록 하는 시스템이다. 현재는 StackOverflow의 자료를 수집하고 데이터베이스에 자동으로 저장하도록 하였다. 수집해야 할 자료가 많아 Celery와 RabbitMQ를 사용하여 비동기 작업을 요청하여 즉시 응답을 받지 않아도 다른 일을 수행할 수 있다. 이렇게 수집한 자료들을 해당 사이트에 나열해줌으로 사용자들이 시간과 비용을 절감하여 효율적인 취업 준비를 할 수 있도록 하는 시스템을 설계 구현하였다.