In this 21st century, the sense of community of the Korean society has been weaken while facing the economic and social problems due to drop in the social capital standards. Due to the supply of smart devices, the problem of digital divide is diffuse ... 
          
          
             In this 21st century, the sense of community of the Korean society has been weaken while facing the economic and social problems due to drop in the social capital standards. Due to the supply of smart devices, the problem of digital divide is diffused in the cyberspace and is causing an acceleration of the social inequality phenomenon through social media. 
 This research project wants to know if the social media has effects to the sophisticated technology that integrates the society’s members and to the formation of trust between them. If that is the case, it is urgently the time for the research regarding the magnification as an important issue of whether the discussion about those influences can be developed. 
 The research team studied about the ways and related policies for the realization of the social integration and the cohesive ecology of the cyber community through social media. In the first year, through studies about the methodology, we prepared the research’s footing about the cohesive ecology of the cyber community and through studies regarding ways to increase the social capital of a community, we conducted early studies about the realization of the cohesive ecology of the cyber community. As representative researches, we proceeded with the experimental study using different text mining and topic modeling techniques in order to analyze big data[1,2], the study on the tracing of social media’s topic changes using Twitter data[3,4], and the study on methods to increase the social capital, primarily based on social media users, through systems thinking approach[5,6]. During the second year, we progressed with the studies on the usage of different techniques for analyzing big data such as topic modeling techniques, word co-occurrence analysis and content-based co-citation techniques, and diverse studies with a goal to establish ways for the realization of the cohesive ecology of the cyber community based on social media from the viewpoints of economics, information systems, and sociology. Specific studies include the Twitter analysis regarding the 2012 Korean Presidential Elections[7,8], methods on social unification to solve the social inequality phenomenon[9], network analysis on the global finance markets using social network analysis approach[10,11], and the analysis of the characteristics of Facebook users[12]. In the third year, we did studies on the planning phase of policies for the realization of the cohesive ecology of the cyber community. We also did interdisciplinary studies about the cyber community social network’s structural characteristics and user types[13,14,15,16] and study on the deduction of economic analysis results targeting social networks[17,18]. 
[1] 박자현, & 송민. (2013). 토픽모델링을 활용한 국내 문헌정보학 연구동향 분석. 정보관리학회지, 30(1), 7-32.
[2] Jeong, D. H., & Song, M. (2014). Time gap analysis by the topic model-based temporal technique. Journal of informetrics, 8(3), 776-790.
[3] 진설아, 허고은, 정유경, & 송민. (2013). 트위터 데이터를 이용한 네트워크 기반 토픽 변화 추적 연구. 정보관리학회지, 30(1), 285-302.
[4] 배정환, 한남기, & 송민. (2014). 토픽 모델링을 이용한 트위터 이슈 트래킹 시스템. 지능정보연구, 20(2), 109-122.
[5] Kwahk, K. Y. (2013). Exploring the Roles of Social Exchanges in Using Information Systems. World Academy of Science, Engineering and Technology, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering, 7(9), 2507-2510.
[6] 손정은, 장윤정, 이소현, & 김희웅. (2013). 시스템사고 접근을 통한 사회적 자본 증대 방안 연구: 소셜미디어 사용자를 중심으로. Information Systems Review, 15(2), 21-40.
[7] 배정환, 손지은, & 송민. (2013). 텍스트 마이닝을 이용한 2012 년 한국대선 관련 트위터 분석. 지능정보연구, 19(3), 141-156.
[8] Song, M., Kim, M. C., & Jeong, Y. K. (2014). Analyzing the political landscape of 2012 Korean Presidential Election in Twitter. Intelligent Systems, IEEE, 29(2), 18-26.
[9] Choi, H. (2013). Social integration and social media. Bangkok international conference on social science.
[10] 김대식, & 곽기영. (2013). 소셜 네트워크 분석 접근법을활용한 글로벌 금융시장 네트워크 분석. 한국경영과학회지, 38(4), 11-33.
[11] 김창식, & 곽기영. (2015). 지식공유 결정요인에 관한 연구. 경영연구, 30, 51-74.
[12] Choi, H. (2013). Interprétation théorique de l'exhibitionnisme sur Facebook: Lipovetsky, Goffman, Beck et Maffesoli. Sociétés, (3), 107-116.
[13] Song, M., Yang, C. C., & Tang, X. (2013). Detecting evolution of bioinformatics with a content and co-authorship analysis. SpringerPlus, 2(1), 1-11.
[14] Jeong, Y. K., Song, M., & Ding, Y. (2014). Content-based author co-citation analysis. Journal of Informetrics, 8(1), 197-211.
[15] Song, M., Kim, S., Zhang, G., Ding, Y., & Chambers, T. (2014). Productivity and influence in bioinformatics: A bibliometric analysis using PubMed central. Journal of the Association for Information Science and Technology, 65(2), 352-371.
[16] 김하진, & 송민. (2014). 동시출현단어 분석을 통한 국내외 정보학 학회지 연구동향 파악. 정보관리학회지, 31(1), 99-118.
[17] 박준형, & 곽기영. 특허 인용 관계가 기업 성과에 미치는 영향: 소셜네트워크분석 관점.
[18] 윤지현, & 곽기영. (2015). 연구논문: 기업 SNS 사용의 선행요인 및 결과요인에 관한연구. 지식경영연구, 16(1), 143-170.