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.
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Within the film and theater world, special effects make-up is used to adapt the appearance of actors for visual storytelling. Currently the creation of special effects makeup is a time-consuming process which creates a lot of waste that doesn’t fit in with the goals of a sustainable industry. Combine with the trend of the digitization of the movie and theater industry which require faster and more iterative workflows, the current ways of creating special effects makeup requires changing. Within this project we would like to explore if the traditional way of working can be converted to a digital production process. Our research consists of three parts. Firstly, we would like to explore if a mobile face scanning rig can be used to create digital copies of actors, and such eliminate the need to creates molds. Secondly, we would like to see if digital sculpting can replace the traditional methods of sculpting molds, casts and prosthetics. Here we would like to compare both methods in terms of creativity and time consumption. The third part of our project will be to explore the use of 3D printing for the creation of molds and prosthetics.
Electronic Sports (esports) is a form of digital entertainment, referred to as "an organised and competitive approach to playing computer games". Its popularity is growing rapidly as a result of an increased prevalence of online gaming, accessibility to technology and access to elite competition.Esports teams are always looking to improve their performance, but with fast-paced interaction, it can be difficult to establish where and how performance can be improved. While qualitative methods are commonly employed and effective, their widespread use provides little differentiation among competitors and struggles with pinpointing specific issues during fast interactions. This is where recent developments in both wearable sensor technology and machine learning can offer a solution. They enable a deep dive into player reactions and strategies, offering insights that surpass traditional qualitative coaching techniquesBy combining insights from gameplay data, team communication data, physiological measurements, and visual tracking, this project aims to develop comprehensive tools that coaches and players can use to gain insight into the performance of individual players and teams, thereby aiming to improve competitive outcomes. Societal IssueAt a societal level, the project aims to revolutionize esports coaching and performance analysis, providing teams with a multi-faceted view of their gameplay. The success of this project could lead to widespread adoption of similar technologies in other competitive fields. At a scientific level, the project could be the starting point for establishing and maintaining further collaboration within the Dutch esports research domain. It will enhance the contribution from Dutch universities to esports research and foster discussions on optimizing coaching and performance analytics. In addition, the study into capturing and analysing gameplay and player data can help deepen our understanding into the intricacies and complexities of teamwork and team performance in high-paced situations/environments. Collaborating partnersTilburg University, Breda Guardians.
Visual Learning from Family Dairy Tech (Based on the RAAK MKB Family Dairy Tech India) Relevance of the project An evaluation of the Rathenau Institute states that Living Labs only can become successful if they show how knowledge is being developed in the Living Lab. The RAAK MKB project Family Dairy Tech was part of the Indo-Dutch Living Lab Baramati-Pune of Van Hall Larenstein and Agricultural Development Trust Baramati. Van Hall Larenstein University is currently participating in a review research program of Living Labs in various countries. In a first analysis of VHL Living Labs, ‘stimulating reflexivity in learning and innovation for sustainability’ was identified as one of the design principles for Living Labs. The results of this top-up project will facilitate the learning process of all stakeholders in the RAAK project, but also will connect the discussions and learning experiences in this specific project with experiences in other Living labs elsewhere in the world. By doing this, it contributes to the important challenge which was identified by the Rathenau Institute, that learning in Living Labs should exceed the location of one specific Living Lab. The results will also contribute to the development of a ‘ (digital)value chain field school’ (based on the FAO- Farmers’Field School concept) which will be developed further in the Living Lab Baramati. Activities In the project, a video will be produced to facilitate visual learning through reflection on the innovative designs and lessons of te RAAK project Family Dairy Tech India. Participants in the Family Dairy Tech India will be interviewed using the Visual Appraisal technique. The participants that will be interviewed comprise in India: two farmers, one researcher and one entrepreneur and in the Netherlands: three researchers, two entrepreneurs and one student. Project team and target group The project team consists of the project leader of the RAAK Family Dairy Tech project and a senior researcher of VHL, that has broad experience with Visual Project Appraisal (VPA) methods in Africa and India. The video will be employed in educational activities of VHL, Saxion and Baramati College (India), VHL’s Living Lab development in other countries and offered to the participating companies for internal learning and to SIA/Nuffic for their Living Labs development. Project result: a video that can facilitate visual learning strategies. Planning: the project will be carried out between February and August 2018
