Authors Name: Xin Song1, Shicheng Zhao2, Xilin Jiang3, Yiheng Sun4, Chengda Lyu5
Given the popularity of Pokemon Go worldwide, a social network analysis method was used to evaluate connections among users. The Twitter historical database was used to search for suitable tweets, and the search term of “Pokémon Go,” and “friends” were used. We used software tool NodeXL, which uses the Twitter API connection to search Twitter database. There were 975 tweets, 790 mentions and 185 replies. There were 1108 closed subgraphs. There were 785 single users which are not connected with anyone. Maximum size of a subgraph was 69 users, and the maximum number of connection in a subgraph was 98. The maximum number of connections to get from one user to another was 6, with the average number of 1.8 connections. It was hard to recognize a clear network structure, but few central users were identified. Most clusters were broadcast networks, and there were many famous individuals or organizations with large numbers of followers that were not closely connected. The network grew over time, and the growth momentum was closely dependent on influential users.
Keywords: Social Network Analysis, Pokemon Go, Twitter, NodeXL
Dids Link : http://dids.info/didslink/07.2017-53976726