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Digital Culture & Society

Editor-in-Chief: Reichert, Ramón

Ed. by Richterich, Annika / Abend, Pabl / Fuchs, Mathias / Wenz, Karin

2 Issues per year

Online
ISSN
2364-2122
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Visual Social Media and Big Data. Interpreting Instagram Images Posted on Twitter

Dhiraj Murthy / Alexander Gross / Marisa McGarry
Published Online: 2016-12-24 | DOI: https://doi.org/10.14361/dcs-2016-0208

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.

Keywords: social media; Instagram; Twitter; image posting; crisis communication; humour; big data

About the article

Published Online: 2016-12-24

Published in Print: 2016-12-01


Citation Information: Digital Culture & Society, ISSN (Online) 2364-2122, ISSN (Print) 2364-2114, DOI: https://doi.org/10.14361/dcs-2016-0208.

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© 2016 by transcript Verlag.

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