Workshop Media Practice Theory Winter 2020/21
Workshops & Lectures in the winter term 2020/21:
Tuesday at 5pm (lecture)
Wednesday at 11am (workshop)
Due to the restrictions because of the COVID-19 pandemic, all lectures and workshops will be held online.
The rise of big data indicates a “watershed moment for the social sciences”. Not only are we faced with large and multifarious types of data (e.g. texts, geo location, time stamps, entire full-text archives, pictures), often very unstructured, and stemming from all sorts of sources and phenomena, we are also challenged in our theoretical underpinnings of what constitutes the social and how we can analyze it. We are also witnessing the rise of methods that help to identify patterns and relations, and to reduce complexity. Tools and algorithms of computational linguistics, machine learning, and network analysis are challenging the traditional tool kits of social science methods, which work with representative samples, independent observations, statistical significance or analysts’ privileged positions in local settings. The talk discusses some of the challenges large-scale textual data pose to sociological analysis. In particular, it highlights challenges of data construction, algorithmic models of data analysis, and data interpretation using examples of empirical studies.
Sophie Mützel is Professor of Sociology at the Department of Sociology, University of Lucerne, Switzerland. She teaches on the sociology of algorithms, big data and social media, as well as on metrics in journalism and the digital economy within the study program “Media and Networks”. Her research interests lie in the areas of big data and its analytics, in particular text analytics and network analysis, as well as economic and cultural sociology. She recently finished a book manuscript on “Markets from stories”. She is the PI of the Swiss federal government funded NRP75 project “Facing big data: methods and skills for a 21st century sociology”. She is also part of an interdisciplinary research group on “Mining for Meaning: The Dynamics of Public Discourse on Migration” funded by the Swedish Research Council.
In this presentation I discuss the intersection of cycling and media. Contrary to the assumption that cycling is an unmediated practice, many media and aesthetic practices can be observed around cycling. Cycling culture ranges from practices of repairing to collective processes, training and geo media apps as well as image media. I would like to use visual media to describe how media affects cycling and vice versa: which practices co-emerge with practices of mobility. I will focus especially on audiovisual approaches. Based on vlogs of women cyclists, the importance of media practices for cycling culture and as potential empowerment will be discussed. Using the practices of cycling and bicycle vlogs, I will combine aesthetic and practical theoretical concepts: Thus I propose to consider infrastructures, images and collective processes as intertwined in the production of cycling.
Julia Bee, Dr. phil, is Junior Professor for image theory at the Bauhaus University in Weimar. Currently she is Mercator fellow at the CRC Media of Cooperation at the University of Siegen. Her fields of work are: Visual anthropology and experimental visual processes, gender and media, philosophies of perception and experience, bicycle media. Current publications: Diffraktion – Individuation – Spekulation. Zur Methodendebatte in den Medienwissenschaften“, in: Zeitschrift für Medienwissenschaft 22, 2020, with Jennifer Eickelmann und Kat Köppert, „Filmische Trans/Individuationen, Ansprache, Affekte und die Konstitution von feministischen Kollektiven in Long Story Short und Yours in Sisterhood, in: nachdemfilm 17, 2019; Gefüge des Zuschauens. Begehren, Macht und Differenz in Film- und Fernsehwahrnehmung, Bielefeld 2018.
In this talk I consider how data walking can be a productive method studies for the study of data and its infrastructures in media and communication studies. I examine how three affordances of walking (embodied, situated and generative) offer opportunities for different forms of knowledge production (experiential, spatio-temporal and performative). Subsequently, I reflect on data walks within a series of new methods for studying data (and its infrastructures) that all emphasize data as situated and offer a distinct form of criticality. To this end I explore “the walkthrough method” (Light, Burgess and Duguay 2018), “local readings” (Loukissas 2019) “situated data analysis” (Rettberg 2020) but also feminist data visualization (D’Ignazio and Klein 2020).
Karin van Es (@kfvanes) is assistant professor in media and culture studies at Utrecht University, the Netherlands. Her research centers on questions of data, tool criticism in computational methods, and the datafication of public service media. She is co-editor of the open-access volume The Datafied Society (Amsterdam University Press, 2017) and the special issue “Big Data Histories” (2018) for TMG- Journal for Media History. She has published in outlets such as Social Media + Society, Television & New Media, Media, Culture & Society and First Monday.