This publication has been realized on the occasion of the project FORMER WEST: Documents, Constellations, Prospects, a joint undertaking by BAK, basis voor actuele kunst, Utrecht and Haus der Kulturen der Welt (HKW),Berlin organized at HKW from 18–24 March 2013.
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This chapter takes a closer look at the case of Amsterdam as a particular manifestation of a film festival city. Drawing from a new dataset on festivals in the Netherlands, the data supports the view of film festivals as a highly dynamic cultural sector: Internationally acclaimed film festivals exist beside smaller festivals that are more community bound; new festivals emerge annually, and young festivals struggle to survive the three-to-five-year mark.Amsterdam holds a unique position in the Dutch film festival landscape as a third of all film festivals in the Netherlands take place in the capital city. Our data collection helps to bring parts of the city’s film infrastructure to the forefront. On the one hand, Amsterdam’s top five locations for film festival events show clear creative cities logic: The data shows just how powerful the pull of such locations is. On the other hand, we find evidence of placemaking and livable city strategies: Amsterdam’s film festivals extend into the capillaries of the city.Dedicated festival datasets may cast new perspectives on local or national festival landscapes, by revealing patterns that remain hidden in qualitative and case-study based projects. But there are also challenges to address in data-driven research on festival cultures, we name a few such as categorization of data. We conclude that such challenges can be more easily faced if more datasets, of for instance, other cities, are pursued and become available.
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Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention towards 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 circulation and contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by networked 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 is limited. However, combining automated analyses of images - broken down by their compositional elements - with repurposing platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This paper explores the capacities of platform data - hashtag modularity 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 by networked publics that co-create meaning.
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