• Convergence Security Journal
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• v.16 no.2
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• pp.25-34
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• 2016

This study aims to prevent the serious threat from dangerous person or group by responding or blocking or separating illegal activities by use of SNA: Social Network Analysis. SNA enables to identify the complex social relation of suspect and individuals in order to enhance the effectiveness and efficiency of investigation. SNS has rapidly developed and expanded without restriction of physical distance and geo-location for making new relation among people and sharing large amount of information. As rise of SNS(facebook and twitter) related crimes, terrorist group 'ISIS' has used their website for promotion of their activity and recruitment. The use of SNS costs relatively lower than other methods to achieve their goals so it has been widely used by terrorist groups. Since it has a significant ripple effect, it is imperative to stop their activity. Therefore, this study precisely describes criminal and terrorist activities on SNS and demonstrates how effectively detect, block and respond against their activities. Further study is also suggested.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.67-73
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• 2015

In this paper, we propose a disconnectedness determination algorithm for workflow-supported enterprise social networks. this networks can be discovered from the work-allocation relationships between activities and performers in workflow procedures and It networks are useful to analyze, evaluate and numerically explain the work-performance of performers. But there could be the disconnectedness due to the characteristics of workflow, and therefore analysis result of performers can be inappropriate logically as well as mathematically. So, we have to decide whether or not this network is disconnectedness before we analyze workflow-supported enterprise social networks. Conclusively, we try to carry out a thorough investigation into the formation reasons of the disconnectedness, and propose a determination algorithm of the disconnectedness for workflow-supported enterprise social networks.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.107-130
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• 2012

In Twitter, a user can post a message below 140 characters on his/her account, and can also repost a message of other users who the user follows. The message posted by the user in turn can be seen and reposted by other users who follow the user, which is called Re-tweet (RT). While some messages spread widely, other messages have relatively less or no RT. What factors cause these quantity variances of RT originated from original messages? How can the messages become influential in online social networks? As an effort to answer the above questions, we focused on information vividness, message characteristics, and originator characteristics. In perspective of managerial implication, we expect that the findings of this paper will provide corporations with helpful insight on the Word-of-Mouth (WOM) effect for efficient and effective advertisements and communications when they send a message of new products or services through Social Network Services. In perspective of academic implication, we identify the effect of contents of a message on WOM, which has been dealt with by few social network researches.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.71-77
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• 2015

This paper implements an estimated closeness centrality ranking algorithm in large-scale workflow-supported social networks and performance analyzes of the algorithm. Existing algorithm has a time complexity problem which is increasing performance time by network size. This problem also causes ranking process in large-scale workflow-supported social networks. To solve such problems, this paper conducts comparison analysis on the existing algorithm and estimated results by applying estimated-driven RankCCWSSN(Rank Closeness Centrality Workflow-supported Social Network). The RankCCWSSN algorithm proved its time-efficiency in a procedure about 50% decrease.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.198-201
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• 2011

본 연구는 현재 널리 사용되고 있는 소셜네트워크 속에서 일반 사용자들이 의료 도메인의 전문가들과 쉽게 질문과 응답을 주고 받을 수 있게 해주는 서비스 개발을 위한 기초 연구로써, 사용자의 문서를 분석하여 질문을 추출해 내고 어떤 의료 도메인에 해당하는 질문인지 분류하는 연구이다. 한글로 구성된 문서 속에서 질문에 해당하는 형태소 분석 방법을 이용하야 질문을 추출을 한 다음 질문 속의 단어 들을 분석하여 KORLEX를 이용한 단어간의 관계성을 분석하여 도메인을 분류하는 작업을 거친다. 또한 본 연구는 텍스트마이닝 기법과 인공지능의 분류 기법을 응용하여 소셜네트워크 속에서 질문과 응답을 분석하여, 의료 도메인의 전문가들이 볼 수 있게 함으로써, 소셜네트워크를 이용한 양방향의 질의응답 서비스를 제공 한다. 이 같은 양방향 질의응답 서비스를 통해 헬스케어 및 의료 관리 서비스를 받을 수 있다. 본 논문은 소셜네트워크 상에서 사용자들이 올린 헬스케어에 관련된 질문들을 추출하고 분류해 주는 과정에 한정하여 진행된 결과를 기술한다.

• Journal of Digital Convergence
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• v.12 no.10
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• pp.243-252
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• 2014

Many researches about the effect on politics, economics and Sociocultural phenomenon using the social media are in progress. Authors utilized NAVER Trend most famous web browsing service in korea, NAVER Blog social media, NAVER Cafe service and Open Data(API) and also used temperature, humidity index data of Korea Meteorological Administration. This study analyzed a change of the public's emotion in korea using Cluster analysis of vocabulary of taste among its of feelings and senses. K-means clustering was followed by decision of the number of groups which was used Chi-square goodness of fit test and ward analysis. Eight groups was made and it represented sensitive vocabulary. By Discriminant analysis, eight groups decided by Cluster analysis has 98.9% accuracy. The change of the public's emotion has capability to predict people's activity so they can share sensibility and a bond of sympathy developed between them.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.295-300
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• 2017

The study evaluates exploration of social robot's role which can emotionally communicate with human as an alternative to heal psychological isolation for single-person households. At first, I conduct a study on literatured to understand the definition and characteristics of social robot then analyze the current situation and future prospects. Based on this, I organized the requirements of social robot in aspect of user experience through in-depth interview of twenties single-person households living in the metropolitan area who could be potential customers. As a result every subject require social robot specialized to them through accumulated interaction. On the other hand, degree of attachment with social robot is different from subjects. Hear by I realize every subject require social robot to different and various functions according to their lifestyle and personality. Therefore I could draw conclusions and implications from this study that technical development in aspect of personalized user experience is necessary for social robot to settle in to human's life in the future.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.215-227
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• 2021

This study empirically studied the factors affecting the intensity of use of mobile social media and fatigue. Theories for the research framework were based on the theory of planned behavior, the theory of private information protection, the theory of flow, and the theory of process incentives. As a result of data analysis, it was found that self-efficacy, user habits, and flow experience positively influence the intensity of mobile social media use. This study assumed that personal information protection issues negatively affect the intensity of mobile social media use, but have little influence on the use intensity. The intensity of media use had a positive effect on media fatigue. In other words, when the intensity of using mobile social media increased, the feeling of fatigue increased. The expected process incentives variable did not show a moderating effect between media use intensity and social media fatigue. The findings will have implications for social media-related companies and organizations that want to use social media tools for business and public services.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.47-60
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• 2021

Since the outbreak of COVID-19 in 2019, the pandemic has been prolonged. This study compares and analyzes the degree of social media usage, the information type of posts (infectious disease information, promote action, psychological communication), and the level of user engagement in conducting crisis communication by country. We conduct text analysis by collecting information on Facebook and YouTube posts from January 2020 to March 2021 of disease control and prevention agencies in Korea, US, UK, and EU. As a result, the use of social media in Korea and US is higher than of the UK and EU, and all four countries are using social media as a means to provide infectious disease information and to promote action. Although social media can be a means to reach the public psychologically, such as sympathy and respect, there are no posts of psychological communication type on social media in countries other than the US. User engagement with posts is highest in the promotion action type. This study can help define the importance and role of social media in establishing an infectious disease crisis communication strategy.

• Journal of Digital Contents Society
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• v.17 no.4
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• pp.295-305
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• 2016

The purpose of this study is to analyze the internal reputation factors that affect the job satisfaction by big data analysis in the social media for corporate reputation and verify the difference between large corporations and small-medium corporations for each factor of internal reputation. The result showed 'Salaries and Benefits' is a major factor that affects the job satisfaction for all research corporations, 'Senior Management' is a major factor for large corporations, and 'Salaries and Benefits' is a major factor for small-medium corporations. As for the difference factors of large corporations and small-medium corporations are 'Job Satisfaction', 'Salaries and Benefits', and 'Work-life Balance'. Unstructured data analysis shows some interesting features to be studied further.