Research on teachers’ use of social media has typically assumed that it is a) driven by a need for professional learning and b) best understood in terms of individual motivations. In this study, we use a dataset of nearly 600,000 tweets posted to one or more of 48 Regional Educational Twitter Hashtags associated with 44 U.S. states. To explore the influence of local contextual factors on hashtag- and account-level activity in these hashtags, we use an analytic approach heretofore uncommon in social media-focussed education research: generalised linear and multilevel modelling. At the hashtag level, higher numbers of teachers within a state, proportions of students receiving subsidised meals, student-to-teacher ratios, and amounts of state spending per child are associated with more activity within a regional hashtag; by contrast, more left-leaning state governments and citizenries are associated with less activity. At the account level, more experienced accounts and accounts in more right-leaning states contribute more tweets to these hashtags. These findings reinforce established understandings of Twitter as a site for teacher learning; however, they also underline the importance of acknowledging other important purposes of teachers’ Twitter use, including receiving emotional support and engaging in activism.

中文翻译：

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政策和环境对教师社交媒体使用的影响

关于教师使用社交媒体的研究通常假设它是 a) 由专业学习的需要驱动的，并且 b) 从个人动机的角度最好地理解。在这项研究中，我们使用了近 600,000 条推文的数据集，这些推文发布到与美国 44 个州相关的 48 个区域教育 Twitter 标签中的一个或多个。为了探索本地上下文因素对这些主题标签中的主题标签和帐户级别活动的影响，我们使用了一种迄今为止在以社交媒体为重点的教育研究中不常见的分析方法：广义线性和多层次建模。在标签层面，一个州内的教师人数越多，接受膳食补贴的学生比例、学生与教师的比例以及每个孩子的州支出金额都与区域标签内的活动越多有关；相比之下，左倾的州政府和公民越多，活动就越少。在账户层面，更有经验的账户和处于更右倾状态的账户为这些主题标签贡献了更多的推文。这些发现加强了人们对 Twitter 作为教师学习网站的既定理解；然而，他们也强调了承认教师使用 Twitter 的其他重要目的的重要性，包括获得情感支持和参与活动。