Online social networks produce a visuality that reflects the attention economy governing this space. What is seen becomes elevated into prominence by networked publics that ‘perform’ affective expressions within platform affordances. We mapped Twitter images of refugees in two language spaces - English and Arabic. Using automated analysis and qualitative visual analysis, we found similar images circulating both spaces. However, photographs generating higher retweet counts were distinct. This highlights the impact of affective affordances of Twitter — in this case retweeting — on regimes of visibility in disparate spheres. Representations of refugees in the English language space were characterized by personalized, positive imagery, emphasizing solidarity for refugees contributing to their host country or stipulating innocence. Resonating images in the Arabic space were less personalized and depicted a more localized visuality of life in refugee camps, with an emphasis on living conditions in refugee camps and the efforts of aid organizations.
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Studying images on social media introduces several challenges that relate to the size of datasets and the different meaning-making grammars of social visuality; or as aptly pointed out by others in the field, it means ‘studying the qualitative on a quantitative scale’. Although cultural analytics provides an automated process through which patterns can be detected in large numbers of images, this methodology doesn’t account for other modalities of the image than the image itself. However, images circulating social media can (and should) be analyzed on the level of their audience as the latter is co-creating the meaning of images. Bridging the study of platform affordances and affect theory, this paper presents a novel methodology that repurposes Facebook Reactions to infer collective attitudes and performative emotional expressions vis á vis images shared on the large Syrian Revolution Network public page (+2M). We found visual patterns that co-occur with certain collective combinations of buttons, displaying how socio-technical features shape the discursive frameworks of online publics.
MULTIFILE
BackgroundWorking in the perioperative context is complex and challenging. The continual evaluation in this environment underscores the need for adaptability to technological advancements, and requires substantial allocation of resources for training and education. This study aimed to explore personality characteristics of nurse anesthetists and surgical nurses that are instrumental for sustainable employability in technologically advanced environment.MethodsExploratory, cross-sectional survey study including nurse anesthetists and surgical nurses, both certified and in training, and a sample of the normative Dutch population. Personality characteristics were identified with the Big Five Inventory, which consisted of 60 items answered on a five-point Likert scale (strongly disagree to strongly agree).ResultsSpecific personality traits were found for nurse anesthetists and surgical nurses when compared to the normative Dutch population. Traits of both nurse anesthetists and surgical nurses differed significantly on all domains of the Big Five Inventory, with the largest differences found within the dimension negative emotionally.ConclusionsThis study highlights the role of specific personality traits in maintaining employability within the rapidly evolving and technologically advanced landscape of healthcare. It emphasizes the relationship between individual traits and professional excellence, being crucial educational strategies for overall improvement in healthcare.
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