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Social network analysis of twitter use during the AERA 2017 annual conference

机译:2017年AERA年会上Twitter使用的社交网络分析

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Social network analysis can provide insight into the educational research community as it manifests and evolves online. This study presents a social network analysis of Twitter use during the American Educational Research Association 2017 Annual Conference. The overall social network is sparse with low density, with a few very active nodes and many unconnected Twitter users. Tweets were positive or neutral and rarely negative. Degree of centrality and of closeness of the top 10 users is high, relative to the top 100 users as centrality, closeness, and betweenness taper off quickly. We interpret this as due to the large number of non-intersecting special interest groups that dilute the overall density of the network. Future social network analysis studies should compare SIGs on various metrics and track their developments over time.
机译:社交网络分析可以在线显示和发展教育研究社区,从而提供洞察力。这项研究在2017年美国教育研究协会年会上提出了Twitter使用的社交网络分析。整个社交网络稀疏且密度低,有几个非常活跃的节点和许多未连接的Twitter用户。推文是正面或中立的,很少是负面的。与排名前100位的用户相比,排名靠前的10个用户的集中度和紧密度较高,因为集中度,紧密度和介于中间的程度会迅速降低。我们将其解释为归因于大量不相交的特殊兴趣组,它们稀释了网络的整体密度。未来的社交网络分析研究应比较各种指标上的SIG,并跟踪其随着时间的发展。

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