Social media is a transformative digital technology, collapsing the “six degrees ofseparation” which have previously characterized many social networks, and breaking down many of the barriers to individuals communicating with each other. Some commentators suggest that this is having profound effects across society, that social media have opened up new channels for public debates and have revolutionized the communication of prominent public issues such as climate change. In this article we provide the first systematic and critical review of the literature on social media and climate change. We highlight three key findings from the literature: a substantial bias toward Twitter studies, the prevalent approaches to researching climate change on social media (publics, themes, and professional communication), and important empirical findings (the use of mainstream information sources, discussions of “settled science,” polarization, and responses to temperature anomalies).Following this, we identify gaps in the existing literature that should beaddressed by future research: namely, researchers should consider qualitativestudies, visual communication and alternative social media platforms to Twitter.We conclude by arguing for further research that goes beyond a focus on sciencecommunication to a deeper examination of how publics imagine climate changeand its future role in social life.
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Abstract: Technological innovation in the healthcare sector is increasing, but integration of information technology (IT) in the care process is difficult. Healthcare workers are important agents in this IT integration. The purpose of this study is to explore factors that feed motivation to use IT. Self-determination theory (SDT) is applied to study how motivational factors impact effective IT use among frontline caregivers in residential care settings. As the team is very important to these caregivers, the team is our unit of analysis. In an embedded single case study design, interviews were conducted with all nine members of a team effectively using IT. All three basic psychological needs from SDT - autonomy, competence and relatedness - were found to have impact on effective IT use, though autonomy was primarily experienced at team level. Conversely, the effective use of an IT collaboration tool influences relatedness.
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Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention toward the computational interpretation of visual data. When analyzing large numbers of images, both traditional content analysis as well as cultural analytics have proven valuable. However, these techniques do not take into account the contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by online publics, bound through networked practices, these visuals should be analyzed on the level of their networked contextualization. Although machine vision is increasingly adept at recognizing faces and features, its performance in grasping the meaning of social media images remains limited. Combining automated analyses of images with platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This article explores the capacities of hashtags and retweet counts to complement the automated assessment of social media images, doing justice to both the visual elements of an image and the contextual elements encoded through the hashtag practices of networked publics.
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