Visual Social Media and Big Data. Interpreting Instagram Images Posted on Twitter
Visual Social Media and Big Data. Interpreting Instagram Images Posted on Twitter
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视觉社交媒体和大数据。
DOI：
10.14361/dcs-2016-0208
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Marisa McGarry
中科院分区：
文献类型：
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作者：
D. Murthy;Alexander Gross;Marisa McGarry
摘要 Twitter 和 Instagram 等社交媒体速度快、免费且多播。 These attributes make them particularly useful for crisis communication.然而，速度和数量也使它们难以研究。从历史上看，记者控制图像代表危机的内容/方式。 Large volumes of social media can change the politics of representing disasters.然而，从方法论上来说，研究视觉社交媒体数据具有挑战性。具体来说，这个过程通常是劳动密集型的，需要使用人类对图像进行编码来辨别主题和主题。因此，调查危机期间社交媒体的研究倾向于检查文本。此外，Instagram 和 Snapchat 等视觉社交媒体服务的应用程序编程接口 (API) 受到限制，甚至不存在。我们的工作使用 Instagram 用户在飓风桑迪期间在 Twitter 上发布的图像作为案例研究。这个特殊案例很独特，因为这可能是美国第一起 Instagram 在受害者如何经历桑迪事件中发挥关键作用的灾难。这也是 Instagram 图片从 Twitter 源中删除之前发生的最后一场美国重大灾难。 Our sample consists of 11,964 Instagram images embedded into tweets during a twoweek timeline surrounding Hurricane Sandy.我们发现，自拍照、食物/饮料、宠物和幽默宏观图像的生产和消费凸显了代表灾难的政治可能发生的变化——从对灾难的自上而下的理解到自下而上的、公民知情的观点的潜在转变。最终，我们认为危机期间产生的图像数据在帮助我们了解灾难的社会经历方面具有潜在价值，但研究这些类型的数据提出了理论和方法上的挑战。
Abstract Social media such as Twitter and Instagram are fast, free, and multicast. These attributes make them particularly useful for crisis communication. However, the speed and volume also make them challenging to study. Historically, journalists controlled what/how images represented crises. Large volumes of social media can change the politics of representing disasters. However, methodologically, it is challenging to study visual social media data. Specifically, the process is usually labour-intensive, using human coding of images to discern themes and subjects. For this reason, Studies investigating social media during crises tend to examine text. In addition, application programming interfaces (APIs) for visual social media services such as Instagram and Snapchat are restrictive or even non-existent. Our work uses images posted by Instagram users on Twitter during Hurricane Sandy as a case study. This particular case is unique as it is perhaps the first US disaster where Instagram played a key role in how victims experienced Sandy. It is also the last major US disaster to take place before Instagram images were removed from Twitter feeds. Our sample consists of 11,964 Instagram images embedded into tweets during a twoweek timeline surrounding Hurricane Sandy. We found that the production and consumption of selfies, food/drink, pets, and humorous macro images highlight possible changes in the politics of representing disasters - a potential turn from top-down understandings of disasters to bottom-up, citizen informed views. Ultimately, we argue that image data produced during crises has potential value in helping us understand the social experience of disasters, but studying these types of data presents theoretical and methodological challenges.