• Title/Summary/Keyword: Social Network Data

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A Group based Privacy-preserving Data Perturbation Technique in Distributed OSN (분산 OSN 환경에서 프라이버시 보호를 위한 그룹 기반의 데이터 퍼튜베이션 기법)

  • Lee, Joohyoung;Park, Seog
    • KIISE Transactions on Computing Practices
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    • v.22 no.12
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    • pp.675-680
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    • 2016
  • The development of various mobile devices and mobile platform technology has led to a steady increase in the number of online social network (OSN) users. OSN users are free to communicate and share information through activities such as social networking, but this causes a new, user privacy issue. Various distributed OSN architectures are introduced to address the user privacy concern, however, users do not obtain technically perfect control over their data. In this study, the control rights of OSN user are maintained by using personal data storage (PDS). We propose a technique to improve data privacy protection that involves making a group with the user's friend by generating and providing fake text data based on user's real text data. Fake text data is generated based on the user's word sensitivity value, so that the user's friends can receive the user's differential data. As a result, we propose a system architecture that solves possible problems in the tradeoff between service utility and user privacy in OSN.

Mission of Social Enterprises in South Korea -A Topic Modeling and Social Network Analysis- (토픽모델링과 사회네트워크분석을 활용한 사회적기업의 미션 연구)

  • Lee, Sae-Mi;Byeon, Jang-Seop;Choi, Ji-Hye;Brown, Alan Dixon
    • Journal of Digital Convergence
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    • v.20 no.4
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    • pp.31-38
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    • 2022
  • The study explores social enterprises' social goals by analysing their mission so as to better understand their perceptions of social problems. Based on the analysis, the study reconsiders the mission of the current era of the Korean social economy. Accordingly, self-disclosed social enterprise data were collected and analyzed using LDA topic modeling and social network analysis methods. Seven mission topics were extracted, and the network centering on key keywords was derived. The analysis results largely divided the social purposes of social enterprises into three categories: 'social purpose that social enterprises want to achieve', 'activities to achieve the purpose', and 'operation method to achieve the purpose'. The study is meaningful in that it emphasizes the importance of establishing and implementing social goals from the point of view of the social economy as well as realizing the economic value of social enterprises by analyzing their mission.

Performance analysis of volleyball games using the social network and text mining techniques (사회네트워크분석과 텍스트마이닝을 이용한 배구 경기력 분석)

  • Kang, Byounguk;Huh, Mankyu;Choi, Seungbae
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.3
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    • pp.619-630
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    • 2015
  • The purpose of this study is to provide basic information to develop a game strategy plan of a team in a future by identifying the patterns of attack and pass of national men's professional volleyball teams and extracting core key words related with volleyball game performance to evaluate game performance using 'social network analysis' and 'text mining'. As for the analysis result of 'social network analysis' with the whole data, group '0' (6 players) and group '1' (11 players) were partitioned. A point of view the degree centrality and betweenness centrality in 'social network analysis' results, we can know that the group '1' more active game performance than the group '0'. The significant result for two group (win and loss) obtained by 'text mining' according to two groups ('0' and '1') obtained by 'social network analysis' showed significant difference (p-value: 0.001). As for clustering of each network, group '0' had the tendency to score points through set player D and E. In group '1', the player K had the tendency to fail if he attack through 'dig'; players C and D have a good performance through 'set' play.

A Study of the Factors influencing User Acceptance of Social Shopping based on Social Network Service (소셜네트워크 서비스 기반의 소셜쇼핑 사용자 수용에 영향을 미치는 요인에 관한 연구)

  • Hwang, Hyun-Seok;Lee, Xintao
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.1
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    • pp.61-71
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    • 2014
  • Recently social shopping, combining e-Commerce with Social Network Service, become a brand-new eBusiness model. In this paper, we aim to identify the structural relationship of the factors affecting the intention of using social shopping. Reviewing the previous works of social shopping, internet shopping and TAM (Technology Acceptance Model), we extract factors affecting the intention of using social shopping and build a structural research model among these factors. To analyze the structural relationship among theses factors, we perform an empirical study - gathering data from a survey and analyzing gathered data using EFA (Exploratory Factor Analysis) and SEM (Structural Equation Model) to identify the structural relationship. We also analyze moderating effect of past experience of social shopping and gender. As a result, We also can find that two factors - Perceived usefulness and Expected enjoyment - are the key factors influencing acceptance of social shopping and that more segmented strategies are required to attract customers since factors affecting Intention to use are somewhat different according to past experience and gender of respondents.

Recommendation Method considering New User in Internet of Things Environment (사물인터넷 환경에서 새로운 사용자를 고려한 정보 추천 기법)

  • Kwon, Joonhee;Kim, Sungrim
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.13 no.1
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    • pp.23-35
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    • 2017
  • With the popularization of mobile devices, the number of social network service users is increasing, thereby the amount of data is also increasing accordingly. As Internet of Things environment is expanding to connect things and people, there is information much more than before. In such an environment, it becomes very important to recommend the necessary information to the user. In this paper, we propose a recommendation method that considers new users in IoT environment. In the proposed method, we recommend the information by applying the centrality-based social network analysis method to the recommendation method using the social relationships in the social IoT. We describe the seven-step recommendation method and apply them to the music circle scenario of the IoT environment. Through the music circle scenario, we show that we can recommend more suitable information to new users in the IoT environment than the existing recommendation method.

Social Network Analysis of author's interest area in Journals about Computer (컴퓨터 분야 논문지에서 저자의 관심분야에 대한 소셜 네트워크 분석)

  • Lee, Ju-Yeon;Park, Yoo-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.1
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    • pp.193-199
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    • 2016
  • Recently there are many researches about analyzing the interaction between entities by social network analysis in various fields. In this paper, we are going to analyze the author's interests area at the biography section in Journal of the Korea Institute of Information and Communication Engineering by social network analysis. The results show that many authors in that journal are mainly focusing on embedded, security, image processing, wireless network, big data, USN, network, RFID.

Framing North Korea on Twitter: Is Network Strength Related to Sentiment?

  • Kang, Seok
    • Journal of Contemporary Eastern Asia
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    • v.20 no.2
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    • pp.108-128
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    • 2021
  • Research on the news coverage of North Korea has been paying less attention to social media platforms than to legacy media. An increasing number of social media users post, retweet, share, interpret, and set agendas on North Korea. The accessibility of international users and North Korea's publicity purposes make social media a venue for expression, news diversity, and framing about the nation. This study examined the sentiment of Twitter posts on North Korea from a framing perspective and the relationship between network strengths and sentiment from a social network perspective. Data were collected using two tools: Jupyter Notebook with Python 3.6 for preliminary analysis and NodeXL for main analysis. A total of 11,957 tweets, 10,000 of which were collected using Python and 1,957 tweets using NodeXL, about North Korea between June 20-21, 2020 were collected. Results demonstrated that there was more negative sentiment than positive sentiment about North Korea in the sampled Twitter posts. Some users belonging to small network sizes reached out to others on Twitter to build networks and spread positive information about North Korea. Influential users tended to be impartial to sentiment about North Korea, while some Twitter users with a small network exhibited high percentages of positive words about North Korea. Overall, marginalized populations with network bonding were more likely to express positive sentiment about North Korea than were influencers at the center of networks.

Trend Analysis of Data Mining Research Using Topic Network Analysis

  • Kim, Hyon Hee;Rhee, Hey Young
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.5
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    • pp.141-148
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    • 2016
  • In this paper, we propose a topic network analysis approach which integrates topic modeling and social network analysis. We collected 2,039 scientific papers from five top journals in the field of data mining published from 1996 to 2015, and analyzed them with the proposed approach. To identify topic trends, time-series analysis of topic network is performed based on 4 intervals. Our experimental results show centralization of the topic network has the highest score from 1996 to 2000, and decreases for next 5 years and increases again. For last 5 years, centralization of the degree centrality increases, while centralization of the betweenness centrality and closeness centrality decreases again. Also, clustering is identified as the most interrelated topic among other topics. Topics with the highest degree centrality evolves clustering, web applications, clustering and dimensionality reduction according to time. Our approach extracts the interrelationships of topics, which cannot be detected with conventional topic modeling approaches, and provides topical trends of data mining research fields.

A Study on Co-authorship Network in the Journals of a Branch of Logistics (물류 분야 학술지의 공저자 네트워크 및 연구주제 분석)

  • Lim, Hye-Sun;Chang, Tai-Woo
    • IE interfaces
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    • v.25 no.4
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    • pp.458-471
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    • 2012
  • In this study, we investigate the cooperative relationships between researchers who have co-authorship in the logistics-related journals in Korea by using social network analysis (SNA). We analyzed the co-authorship data of 781 articles published from 2005 to 2011 in four journals of 'Logistics Study', 'Journal of Korean Society of SCM', 'Korea Logistics Review' and 'Journal of Shipping and Logistics.' We examined the trend of cooperative research in the field of logistics with basic data of the co-authorship network. Then, we analyzed structural properties of the network and the sub-networks of research groups having co-authorship. We could verify the authors who play important roles within the network by using SNA indicators. In addition, we constructed the keyword networks based on the keyword data of all articles by research groups in order to understand the research topics of each group, and thereby we could draw several implications on the cooperative researches in the field of logistics.

The Relationships among Loneliness, Social Support, and Family Function in Elderly Korean (노인의 외로움과 사회적지지, 가족기능간의 관계 연구)

  • 김옥수;백성희
    • Journal of Korean Academy of Nursing
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    • v.33 no.3
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    • pp.425-432
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    • 2003
  • Purpose: To examine the relationships among loneliness, social support, and family function in elderly Korean. Method: The sample for this study were 290 elderly Korean who were at least 60 years of age. Data were collected by interview using the translated Korean versions of the Revised University of California Los Angels Loneliness Scale(RULS), Family APGAR, and Social Support Questionnaire 6. Result: Subjects were moderately lonely and had moderately functional families. Means for social support were 1.42 for network size and 4.09 for satisfaction. Subjects who lived with their spouses had a larger number of network members than who did not live with spouses. However, living with spouses was not associated with social support satisfaction. The level of loneliness was related negatively to the level of social support network, social support satisfaction and family function in this study. Social support satisfaction and Family function were the significant predictor of loneliness. Conclusion: The number of social supporter and satisfaction and family function should be considered in nursing intervention to decrease the level of loneliness in older adults. Further studies and efforts will be needed to reduce the level of loneliness in older adults.