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首页> 外文期刊>BMC Medical Informatics and Decision Making >Social media engagement analysis of U.S. Federal health agencies on Facebook
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Social media engagement analysis of U.S. Federal health agencies on Facebook

机译：美国联邦卫生机构在Facebook上的社交媒体参与度分析

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Background It is becoming increasingly common for individuals and organizations to use social media platforms such as Facebook. These are being used for a wide variety of purposes including disseminating, discussing and seeking health related information. U.S. Federal health agencies are leveraging these platforms to ‘engage’ social media users to read, spread, promote and encourage health related discussions. However, different agencies and their communications get varying levels of engagement. In this study we use statistical models to identify factors that associate with engagement. Methods We analyze over 45,000 Facebook posts from 72 Facebook accounts belonging to 24 health agencies. Account usage, user activity, sentiment and content of these posts are studied. We use the hurdle regression model to identify factors associated with the level of engagement and Cox proportional hazards model to identify factors associated with duration of engagement. Results In our analysis we find that agencies and accounts vary widely in their usage of social media and activity they generate. Statistical analysis shows, for instance, that Facebook posts with more visual cues such as photos or videos or those which express positive sentiment generate more engagement. We further find that posts on certain topics such as occupation or organizations negatively affect the duration of engagement. Conclusions We present the first comprehensive analyses of engagement with U.S. Federal health agencies on Facebook. In addition, we briefly compare and contrast findings from this study to our earlier study with similar focus but on Twitter to show the robustness of our methods.
机译：背景技术个人和组织使用诸如Facebook之类的社交媒体平台变得越来越普遍。这些用于各种各样的目的，包括传播，讨论和寻求与健康有关的信息。美国联邦卫生机构正在利用这些平台来“吸引”社交媒体用户阅读，传播，促进和鼓励与健康相关的讨论。但是，不同的机构及其通信会获得不同程度的参与。在这项研究中，我们使用统计模型来识别与参与相关的因素。方法我们分析了来自24个卫生机构的72个Facebook帐户中的45,000个Facebook帖子。研究这些帖子的帐户使用情况，用户活动，情绪和内容。我们使用跨栏回归模型来确定与参与程度相关的因素，并使用Cox比例风险模型来确定与参与持续时间相关的因素。结果在我们的分析中，我们发现代理商和客户在社交媒体的使用和产生的活动方面差异很大。例如，统计分析表明，Facebook帖子具有更多视觉线索，例如照片或视频，或者表达积极情绪的帖子，会产生更多的参与度。我们进一步发现，有关某些主题（例如职业或组织）的帖子会对参与时间产生负面影响。结论我们在Facebook上首次对与美国联邦卫生机构的互动进行了综合分析。此外，我们简要比较和对比了本研究与我们先前的研究结果，重点类似，但在Twitter上显示了我们方法的鲁棒性。

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