• Title/Summary/Keyword: usage of social networking communities

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Inculcating a Sense of Community Among Members of Social Networking Communities

  • Gupta, Sumeet;Kim, Hee-Woong;Lee, So-Hyun
    • Knowledge Management Research
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    • v.16 no.4
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    • pp.89-108
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    • 2015
  • Social networking communities (SNCs) are media designed to facilitate social interaction using highly accessible and scalable publishing techniques. SNCs can constitute individuals' their own profiles in the online environment and share texts, images and photos in a variety ways. In other words, one of the other motivators is knowledge sharing. Various sites, such as Facebook, Orkut, MySpace, and Hi5 are categorized as SNCs. SNCs have become increasingly popular in recent years among youths, especially students, who use them to build social networks. This study examines whether this usage of SNCs inculcates a sense of community among their members. Several studies have examined the role of a sense of community through increased usage in the context of virtual communities. Although this result may be true of virtual communities, this paper contends that the opposite relationship prevails in the case of SNCs because members interact to build networks and are not obliged to interact. The results reveal that maintaining long-term interactions in the SNCs is helpful in building a sense of community in SNCs. Although short-term usage may not boost the development of a sense of community in SNCs, it does matter if the premise is for a long-term commitment to SNCs. Implications for theory and practice are discussed.

A qualitative Study of successful community networking experiences of social workers (지역사회 네트워킹(community networking) 형성·유지경험에 관한 질적 연구)

  • Jeong, Jeong-Ho
    • Korean Journal of Social Welfare Studies
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    • v.45 no.2
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    • pp.289-325
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    • 2014
  • In spite of theoretical logics about the necessities and effects of community networking, we have easily watched the failure of netwoking efforts and break of community networks in everyday life. Starting from these experiences, I tried to understand the process of community networking from the networkers'point of view, by the qualitative research method. Through qualitative in-depth interviews on the 6 experienced social workers in 4 communities, I analyzed their experiences of community network building, presented the results(practical guidelines), especially for the social workers expecting to be a community netwoker themselves. They consist of 10 categories and 5 themes(Being a leader/leaderships, partnership/teamwork building, understanding the impact of context, resource usage, netwoking sustaining).

Offline Friend Recommendation using Mobile Context and Online Friend Network Information based on Tensor Factorization (모바일 상황정보와 온라인 친구네트워크정보 기반 텐서 분해를 통한 오프라인 친구 추천 기법)

  • Kim, Kyungmin;Kim, Taehun;Hyun, Soon. J
    • KIISE Transactions on Computing Practices
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    • v.22 no.8
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    • pp.375-380
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    • 2016
  • The proliferation of online social networking services (OSNSs) and smartphones has enabled people to easily make friends with a large number of users in the online communities, and interact with each other. This leads to an increase in the usage rate of OSNSs. However, individuals who have immersed into their digital lives, prioritizing the virtual world against the real one, become more and more isolated in the physical world. Thus, their socialization processes that are undertaken only through lots of face-to-face interactions and trial-and-errors are apt to be neglected via 'Add Friend' kind of functions in OSNSs. In this paper, we present a friend recommendation system based on the on/off-line contextual information for the OSNS users to have more serendipitous offline interactions. In order to accomplish this, we modeled both offline information (i.e., place visit history) collected from a user's smartphone on a 3D tensor, and online social data (i.e., friend relationships) from Facebook on a matrix. We then recommended like-minded people and encouraged their offline interactions. We evaluated the users' satisfaction based on a real-world dataset collected from 43 users (12 on-campus users and 31 users randomly selected from Facebook friends of on-campus users).