• Journal of Information Technology Services
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• v.13 no.4
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• pp.189-203
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• 2014

With the evolution of Internet technologies and the increasing variety of Internet devices, advertisements in various web services have also expanded. Interactive web services often go hand in hand with effective advertisements for a business model. We estimated statistical parameters of the interactive web server for service monitoring and advertisement-effect. In the web pages, we integrated the plugins of social networking services (SNSs) (e.g. Facebook, Twitter) and an advertisement scheme (e.g. Google AdSense) that regards social name-directory contents. Empirical data analysis and statistical results are presented with the implementation of estimations of parameters (e.g. utilization-level and serviceability) and advertisements in a social networking name-directory service (http://ktrip.net or http://한국.net). We found that estimated parameters were applicable to service monitoring of web-server as well as to synthesis of advertisement-effect in our social-web name-directory service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.781-782
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• 2015

As growth engines such as cloud, social networks, big data that can affect the security market have been grown, the information security industry has has also rapidly evolved. Reviewing information security policies carried out in USA, UK and Japan, this paper examines trends on the IoT-related information protection law and regulations that are at issue around the major developed countries. Through this research, we can get the implication that measures be taken as soon as possible to apply the existing data protection laws in the Internet of Things.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.316-321
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• 2010

웹 2.0의 기술이 보급됨에 따라 소셜 네트워크 서비스에 대한 관심이 증가하였다. 국내에서는 싸이월드, 미투데이 등과 같은 서비스가 널리 사용되고 있으며 최근 급부상한 트위터는 여러 분야에서 관심을 받고 있다. 트위터는 팔로워나 트윗 등 활동 정도에 따라 랭킹 서비스가 제공되고 있지만 랭킹은 그들 사이의 관계를 세부적으로 나타내지 못한다. 본 논문에서는 트위터의 사용자들 사이에 존재하는 관계를 시각적으로 나타내는 도구에 대해 개발한다. 국내 사용자 중 팔로워의 랭킹에 따른 사용자를 이용하고, 시각화를 위해 생물학적 데이터를 네트워크로 나타내는 Cytocape 플랫폼을 사용한다. 사용자 간의 관계를 나타내는 네트워크를 통하여 온라인상에서 영향력 있는 사용자들의 관계를 나타내고 그들의 관계를 수치로 분석한다. 또한 복잡한 네트워크로부터 선택된 노드와 관련된 연결만을 추출하는 기능을 제공하여 온라인상의 관계를 상세하게 나타낸다.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.277-278
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• 2013

최근 사회적으로 이슈가 되고 있는 소셜 네트워크 서비스 활용하는 시각 장애인의 수가 점차 증가하고 있으나, 시각 장애인들에 대한 배려 및 접근성은 낙제 수준에 머물고 있다. 이는 보편적인 활용성의 측면보다는 일반인만을 대상으로 제작된 것으로 시각장애인이 원활하게 이용하기에 어려움이 존재한다. 본 논문에서는 시각장애인의 SNS 활용을 지원하기 위한 SNS 관리 시스템을 설계하고 구현한다. 제안하는 시스템은 현재 가장 많은 활용도를 보이는 세 개의 SNS의 공통 특성 분석을 통한 통합 포스팅 관리 및 포스팅 공유 기능을 제공하여 개별 관리 도구 개발에서 발생하는 개발 비용을 감소시키는 것이 가능하다. 또한, 수집 데이터를 시각 장애인의 특성을 고려한 인터페이스로 제공함으로써 시각 장애인의 활용성을 극대화 하였다. 뿐만 아니라, 제안하는 시스템은 독립적인 프로그램의 형태로 제공되기 때문에, 기존의 시각 장애인이 보유하고 있는 보조 기기에 탑재하여 활용하는 것이 가능하다.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.696-699
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• 2014

최근 소셜 네트워크 서비스가 확산되면서 대량 트랜잭션 환경에서의 RDBMS 성능에 대한 관심이 높아지고 있다. 본 논문에서는 대량 트랜잭션 환경에서 DBMS가 SQL문을 처리하면서 발생시키는 I/O의 특징을 고려하여 데이터의 쓰기 블록 수와 트랜잭션 간에 발생하는 배타적 Lock의 빈도를 최소화시키기 위한 모델링을 제안하고 일반적인 모델링과 성능 비교 실험을 하였다. 실험 분석 결과 DBMS의 트랜잭션 처리량이 많고 트랜잭션 간의 교착 빈도가 높게 발생할수록 일반적인 모델링보다 제안하는 모델링에서의 SQL문 처리 성능이 우수하였다.

• Review of KIISC
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• v.29 no.3
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• pp.29-36
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• 2019

폭발적으로 성장하는 소셜 미디어 서비스로 인해 개인간의 연결이 강화된 환경에서는 URL로써 전파되는 피싱 공격의 위험성이 크게 강조된다. 최근 텍스트 분류 및 모델링 분야에서 그 성능을 입증받은 딥러닝 알고리즘은 피싱 URL의 구문적, 의미적 특징을 각각 모델링하기에 적절하지만, 기존에 사용하는 규칙 기반 앙상블 방법으로는 문자와 단어로부터 추출되는 특징간의 비선형적인 관계를 효과적으로 융합하는데 한계가 있다. 본 논문에서는 피싱 URL의 구문적, 의미적 특징을 체계적으로 융합하기 위한 컨볼루션 신경망 기반의 퓨전 신경망을 제안하고 기계학습 방법 중 최고의 분류정확도 (0.9804)를 달성하였다. 학습 및 테스트 데이터셋으로 45,000건의 정상 URL과 15,000건의 피싱 URL을 수집하였고, 정량적 검증으로 10겹 교차검증과 ROC커브, 정성적 검증으로 오분류 케이스와 딥러닝 내부 파라미터를 시각화하여 분석하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.37-40
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• 2019

On this paper, we show the way of forming graph data structure via setting an edge between Korean actors if they appeared in the same movie. From this graph, we calculate the 'centralities' (which declared on this paper) for each actor, then examine distribution by ranking the actors of the centralities and analyze the change of the actor who is/was center on the graph by years. Finally, we suggest the way that sets the numerically Range limits on social group.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1192-1201
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• 2021

This study focused on how to analyze the ICT policy formation process using social big data. Specifically, in this study, a method for quantifying variables that influenced policy formation using the concept of a policy triggering mechanism and elements necessary to present the analysis results were proposed. For the analysis of the ICT policy triggering mechanism, variables such as 'Scope', 'Duration', 'Interactivity', 'Diversity', 'Attention', 'Preference', 'Transmutability' were proposed. In addition, 'interpretation of results according to data level', 'presentation of differences between collection and analysis time points', and 'setting of garbage level' were suggested as elements necessary to present the analysis results.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.41-61
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• 2020

China's rapid development and commercialization of high-tech technologies in the fourth industrial revolution has led to effective technology exchanges between Korean and Chinese firms becoming more important to Korea's mid-term and long-term industrial development. However, there is still a lack of empirical research on how technology exchanges between Korean and Chinese firms proceed and their effectiveness. In response, this study conducted a social network analysis based on text mining data of Korea-China business technology exchange and cooperation articles introduced in the news from 2018 to March 2020 on the current status and effects of Korea-China technology exchanges related to the fourth industrial revolution, and conducted a regression analysis how network centrality effect on the firm performance. According to the results, most of the Korean major electronic firms are actively networking with Chinese firms and institutions, showing high centrality in the centrality index. Korean telecommunication firms showed high betweenness centrality and subgraph centrality, and Korean Internet service providers and broadcasting contents firms showed high eigenvector centrality. In addition, Chinese firms showed higher betweenness centrality than Korean firms, and Chinese service firms showed higher closeness centrality than manufacturing firms. As a result of regression analysis, this network centrality had a positive effect on firm performance. To the best of our knowledge, this is the first to analyze the impact of the technical cooperation between Korean and Chinese firms under the fourth industrial revolution context. This study has theoretical implications that suggested the direction of social network analysis-based empirical research in global firm cooperation. Also, this study has practical implications that the guidelines for network analysis in setting the direction of technical cooperation between Korea and China by firms or governments.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.331-350
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• 2022

This study aims to understand topics of incivility related to COVID-19 from analyzing Twitter posts including COVID-19-related hate speech. To achieve the goal, a total of 63,802 tweets that were created between December 1st, 2019, and August 31st, 2021, covering three targets of hate speech including region and public facilities, groups of people, and religion were analyzed. Frequency analysis, dynamic topic modeling, and keyword co-occurrence network analysis were used to explore topics and keywords. 1) Results of frequency analysis revealed that hate against regions and public facilities showed a relatively increasing trend while hate against specific groups of people and religion showed a relatively decreasing trend. 2) Results of dynamic topic modeling analysis showed keywords of each of the three targets of hate speech. Keywords of the region and public facilities included "Daegu, Gyeongbuk local hate", "interregional hate", and "public facility hate"; groups of people included "China hate", "virus spreaders", and "outdoor activity sanctions"; and religion included "Shincheonji", "Christianity", "religious infection", "refusal of quarantine", and "places visited by confirmed cases". 3) Similarly, results of keyword co-occurrence network analysis revealed keywords of three targets: region and public facilities (Corona, Daegu, confirmed cases, Shincheonji, Gyeongbuk, region); specific groups of people (Coronavirus, Wuhan pneumonia, Wuhan, China, Chinese, People, Entry, Banned); and religion (Corona, Church, Daegu, confirmed cases, infection). This study attempted to grasp the public's anti-citizenship public opinion related to COVID-19 by identifying domestic COVID-19 hate targets and keywords using social media. In particular, it is meaningful to grasp public opinion on incivility topics and hate emotions expressed on social media using data mining techniques for hate-related to COVID-19, which has not been attempted in previous studies. In addition, the results of this study suggest practical implications in that they can be based on basic data for contributing to the establishment of systems and policies for cultural communication measures in preparation for the post-COVID-19 era.