Abstract
Modern internet technologies open a wide range of opportunities for enterprises: keeping accounts online, connecting with customers from different locations, collecting and analyzing data about their target audience and other advantages. One of the actively explored factors related to the potential success is using the Internet tools for projects presentation. The aim of this study is to identify the network distinctive patterns forming the strategies for running and maintaining an online shop’s profile on Russian social networking site vk.com. We collected data about 706 e-shops profiles on vk.com including their descriptions, information about the communities followers and posts on profile wall. For each profile we built an ego graph of followers network and calculated its centrality measures which were further used to run the k-means clustering algorithm. As a result, we identified six distinct clusters which we assume will approximate different strategies of maintaining an e-shop. These clusters differed in terms of important profile features such as community’s audience size, posting activity, followers network connectivity, the presence of “hubs", e-shops operating mostly on vk.com or having an external head website. Considering the network-structure patterns as a result of an online shop’s formed strategy, the potential success can be estimated. Taking a monthly number of visits to a website from vk.com as a success metrics, it turns out that the centrality’s indicators themselves and generalized clusters have associations with a site-visiting frequency.
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Notes
- 1.
- 2.
Profile’s description and demographic information of the community’s followers.
- 3.
Information published on the community’s wall.
- 4.
Structure and centrality measures of the graph-organized data with the online-relations between the followers.
- 5.
An edge (or a node) is called a“bridge” if it connects several relatively big network components.
- 6.
A node is called“hub” if it has relatively high number of connections to other nodes.
References
Baron, R.A.: Psychological perspectives on entrepreneurship: cognitive and social factors in entrepreneurs’ success. Curr. Dir. Psychol. Sci. 9(1), 15–18 (2000)
Box, G.E., Cox, D.R.: An analysis of transformations. J. R. Stat. Society. Ser. B (Methodol.) 211–252 (1964)
Cenek, J., Smolk, J., Svatosovd, V.: Marketing on social networks: content analysis of Facebook profiles of selected Czech e-shops. Trendy Ekonomiky a Managementu 10(26), 9 (2016)
Edmiston, K.: The role of small and large businesses in economic development (2007)
Hartigan, J.A., Wong, M.A.: Algorithm AS 136: a k-means clustering algorithm. J. R. Stat. Soc. Ser. C (Appl. Stat.) 28(1), 100–108 (1979)
Hopkins, J.L.: Can Facebook be an effective mechanism for generating growth and value in small businesses? J. Syst. Inf. Technol. 14(2), 131–141 (2012)
Katz, M.L., Shapiro, C.: Network externalities, competition, and compatibility. Am. Econ. Rev. 75(3), 424–440 (1985)
Katz, M.L., Shapiro, C.: Product introduction with network externalities. J. Ind. Econ., 55–83 (1992)
Lim, K.H., Sia, C.L., Lee, M.K., Benbasat, I.: Do I trust you online, and if so, will I buy? An empirical study of two trust-building strategies. J. Manag. Inf. Syst. 23(2), 233–266 (2006)
Meylakhs, P., Rykov, Y., Koltsova, O., Koltsov, S.: An AIDS-denialist online community on a Russian social networking service: patterns of interactions with newcomers and rhetorical strategies of persuasion. J. Med. Internet Res. 16(11) (2014)
Quan, X.: Prior experience, social network, and levels of entrepreneurial intentions. Manag. Res. Rev. 35(10), 945–957 (2012)
Rochet, J.C., Tirole, J.: Defining two-sided markets. mimeo, IDEI, Toulouse, France, January 2004
Rochet, J.C., Tirole, J.: Two sided markets: a progress report. RAND J. Econ. 37(3), 645–667 (2006)
Rykov, Y., Koltsova, O., Meylakhs, P.: Structure and functions of online communities network mapping of HIV-relevant groups in VK.com SNS. Sotsiologicheskie Issledovaniia, 8 (2016)
Rysman, M.: The economics of two-sided markets. J. Econ. Perspect. 23(3), 125–143 (2009)
Song, Y.: From offline social networks to online social networks: changes in entrepreneurship. Informatica Economica 19(2), 120 (2015)
Spiller, P., Lohse, G.L.: A classification of Internet retail stores. Int. J. Electron. Commer. 2(2), 29–56 (1997)
Swamynathan, G., Wilson, C., Boe, B., Almeroth, K., Zhao, B.Y.: Do social networks improve e-commerce? A study on social marketplaces. In: Proceedings of the First Workshop on Online Social Networks, pp. 1–6. ACM, August 2008
Wennekers, S., Thurik, R.: Linking entrepreneurship and economic growth. Small Bus. Econ. 13(1), 27–56 (1999)
Wong, P.K., Ho, Y.P., Autio, E.: Entrepreneurship, innovation and economic growth: evidence from GEM data. Small Bus. Econ. 24(3), 335–350 (2005)
R Core Team: R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/
RStudio Team: RStudio: Integrated Development for R. RStudio Inc., Boston. http://www.rstudio.com/
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The article was prepared within the framework of the Academic Fund Program at the National Research University Higher School of Economics (HSE) in 2017 2019 (grant No. 17-05-0024).
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Dornostup, O., Suvorova, A. (2018). Network Structure of e-Shops Profile as Factor of Its Success: Case of VK.com. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11186. Springer, Cham. https://doi.org/10.1007/978-3-030-01159-8_4
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