Social media have become important platforms for residents to engage with their neighborhood. This paper investigates two Facebook communities that focus in distinctly different ways on Amsterdam-Noord, a gentrifying neighborhood in Amsterdam. Dialogue on both Facebook communities is found to be thoroughly affective, but the kinds of emotions and the way such emotions are generated and shared differ. Through this analysis, this paper seeks to understand how “affective publics” emerge through a specific form of collaborative storytelling, characterized by tone, form as well as rhythm of online interaction. We show how the channeling of affective expression and attunement helps to build two dissimilar collaborative discourses of the neighborhood transformation. We propose the term online affective placemaking to study and articulate such processes. The term points to mediated feelings and urgency to engage, which bonds participants and impacts the social and political landscape within the neighborhood.
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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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The past decades have shown an accelerated development of technology-enhanced or digital education. Although an important and recognized precondition for study success, still little attention has been paid to examining how an affective learning climate can be fostered in online training programs. Besides gaining insight into the dynamics of affective learning itself it is of vital importance to know what predicts trainees’ intention to transfer new knowledge and skills to other contexts. The present study investigated the influence of five affective learner characteristics from the transfer literature (learner readiness, motivation to learn, expected positive outcomes, expected negative outcomes, personal capacity) on trainees’ pre-training transfer intention. Participants were 366 adult students enrolled in an online course in information literacy in a distance learning environment. As information literacy is a generic competence, applicable in various contexts, we developed a novel multicontextual transfer perspective and investigated within one single study the influence of the abovementioned variables on pre-training transfer intention for both the students’ Study and Work contexts. The hypothesized model has been tested using structural equation modeling. The results showed that motivation to learn, expected positive personal outcomes, and learner readiness were the strongest predictors. Results also indicated the benefits of gaining pre-training insight into the specific characteristics of multiple transfer contexts, especially when education in generic competences is involved. Instructional designers might enhance study success by taking affective transfer elements and multicontextuality into account when designing digital education.
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