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- W2890978497 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." @default.
- W2890978497 created "2018-09-27" @default.
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- W2890978497 date "2018-01-01" @default.
- W2890978497 modified "2023-10-06" @default.
- W2890978497 title "Network Structure of e-Shops Profile as Factor of Its Success: Case of VK.com" @default.
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- W2890978497 doi "https://doi.org/10.1007/978-3-030-01159-8_4" @default.
- W2890978497 hasPublicationYear "2018" @default.
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