Community Formation in Social Network Service (SNS)

MATSUDA Naoko
Fellow, RIETI

Social Network Service (SNS) has recently dramatically increased the number of its users. Thanks to facebook, mixi, linkedin, and other services, we can now enjoy sharing videos and recent events in real time with our friends and families who live far away. This column considers the principle of formation of communities within these SNSs.

Communities in SNS refer to groups of users who share common hobbies and interests through SNS. An attractive community (high reliability and functionality, wealth of information, etc.) is one of the motives for users to participate in an SNS. Designing a system to enable the formation of attractive communities leads to the prosperity of the SNS. This is why a study of the principle of community formation becomes necessary.

Research on Community Formation in SNS

Research on community formation in SNS is said to have started when L.A. Adamic published his research on how users behaved and the kind of community that resulted from such behaviors on an SNS called Club Nexus which was used within Stanford University. L.A. Adamic et al. (2003) clarified that communities created for narrow fields of interest (for example, Latin dancing rather than more general interests such as camping) made stronger connections within the community.

The process of community formation is analyzed by Matsuo and Yasuda (2007) using mixi data. At the time of analysis (2006), communities popular on mixi were those with useful website information or interesting/funny videos, or those that attracted people's attention because of their wide-ranging topics such as one for Mac users. These popular communities expanded with time and gradually diverged into more segmented communities (for example, from Mac in general to iBook specifically). Users feel comfortable in moderate-scale communities in which their own interests can be shared more precisely.

Matsuo and Yasuda (2007) also conducted analysis with regard to the relationship with the real world by analyzing individual connectedness within communities. They clarified the fact that high connectedness (the ratio of actual friendship relations or the number of friendship relations within the community; in a community consisting of n number of members, a maximum of n(n-1)/2 sets of friendship relations can exist) leads to real-world interaction (offline meetings, etc.).

Furthermore, L. Backstrom et al. (2006) created a model to estimate the likelihood of a user joining a community, using LiveJournal which is an SNS consisting mostly of blogs, journals, or diaries. According to this model, the tendency of an individual to join the community increases if he or she has more friends in that community, and if those friends are more connected to one another. The key to joining a community is the trust, or sense of security, in that group.

Regarding friendship relations on SNSs, K. Lewis et al (2008), using facebook data, clarified that friends who had exchanged photographs of themselves on an SNS have strong similar tastes in movies, music, books, and other interests, and formed stronger bonds than those who did not exchange photographs. Although the converse is not always true, there is a high possibility that facilitating the posting of photographs for close friendships will become an important factor from the perspective of SNS system design.

As research into communities that have a positive impact on entrepreneurial activities, S. Nann et al. (2010) used 12 university alumni networks on a German business SNS called Xing and analyzed which alumni community generated entrepreneurial success among graduates. According to this research, entrepreneurs tended to succeed more in a community with a nature less open to the outside and instead with intimate human relationships within the alumni networks. It is thought that when trust exists within a community, raising funds and recruiting human resources become easy. However, when categorizing entrepreneurial success by corporate scale and other factors into five levels, it was found that most successful entrepreneurs have a lower degree of exclusiveness to the outside compared to those on the level just below them, although the difference was slight.

Aiming for SNS Community Formation that Promotes Entrepreneurial Activity

By accumulating this kind of research on community formation, we can expect to recruit more users into SNS communities, expand friendships, activate information exchanges, and further lead to real network formation.

Among the many communities, the author is paying particular attention to those for entrepreneurs. An ideal network that enables entrepreneurs to succeed, using Nishiguchi's (2007) words, is a well-balanced "long-distance companionship and relations with neighbors." If there was an SNS community that would deepen entrepreneurs' everyday relations with their neighbors and accomplish such long-distance relations as cross-industrial social events and business matching, it would undoubtedly contribute to the promotion of entrepreneurial activities.

October 5, 2011
Reference(s)
  • Nishiguchi, Toshihiro (2007), Enkyorikosai to Kinjozukiai: Seiko suru soshiki network senryaku [Global Neighborhoods: Strategies of successful organizational networks], NTT Publishing Co., Ltd.
  • Matsuo, Y., and Y. Yasuda (2007), "SNS ni Okeru Kankei Keisei Genri: mixi no deeta bunseki [Principles of Relation Formation within SNSs: Data analysis of mixi]" Jinko Chino Gakkai Ronbunshi [Journal of the Japanese Society for Artificial Intelligence] volume 22, 5G
  • Blackstrom, L., D. Huttenlocher, X. Lan, and J.Kleinberg (2006), "Group Formation in Large Social Networks: Membership, growth and evolution" in Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
  • Lewis, K., J. Kaufman, M. Gonzalez, A. Wimmer, and N. Christakis (2008), "Tastes, Ties, and Time: A new social network dataset using facebook.com," Social Networks 30 330-342
  • Adamic, L.A., O. Buyukkokten and E. Adar (2003), "A Social Network Caught in the Web," First Monday Volume 8 No.6.
  • Nann, S., J. Krauss, M. Schober, P. A. Gloor, K. Fischbach, and H. Fuhres (2010), "Comparing the Structure of Virtual Entrepreneur Networks with Business Effectiveness," Procedia Social and Behavioral Sciences Volume 2, Issue 4, 6483-6496

October 5, 2011

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