For a situational analytics: An interpretative methodology for the study of situations in computational settings

Abstract

This article introduces an interpretative approach to the analysis of situations in computational settings called situational analytics. I outline the theoretical and methodological underpinnings of this approach, which is still under development, and show how it can be used to surface situations from large data sets derived from online platforms such as YouTube. Situational analytics extends to computationally-mediated settings a qualitative methodology developed by Adele Clarke, Situational Analysis (2005), which uses data mapping to detect heterogeneous entities in fieldwork data to determine ‘what makes a difference’ in a situation. Situational analytics scales up this methodology to analyse situations latent in computational data sets with semi-automated methods of textual and visual analysis. I discuss how this approach deviates from recent analyses of situations in computational social science, and argue that Clarke’s framework renders tractable a fundamental methodological problem that arises in this area of research: while social researchers turn to computational settings in order to analyse social life, the social processes unfolding in these envirnoments are fundamentally affected by the computational architectures in which they occur. Situational analytics offers a way to address this problematic by making a heterogeneously composed situation – involving social, technical and media elements – the unit of computational analysis. To conclude, I show how situational analytics can be applied in a case study of YouTube videos featuring intelligent vehicles and discuss how situational analysis itself needs to be elaborated if we are to come to terms with computational transformations of the situational fabric of social life.

Online, offline, hybrid: Methodological reflection on event ethnography in (post-)pandemic times

“…Accordingly, we developed a framework that is general enough to be applied to different event formats and hybrid event ecologies, and that is attentive to transdisciplinary research contexts as it raises questions that apply to all event participants alike. While it still remains an open question how the increase in virtual interactions in (post-)pandemic times will affect the socio-political processes in our research fields and our ethnographic practice ( Lupton, 2021 ), our framework is also open to methods of virtual and digital ethnography ( Hine, 2000 ) and “situational analytics,” which use data mapping strategies and tools ( Marres, 2020 ). While virtual settings offer radically different data collection opportunities, digital methods can help us to open-mindedly explore virtual event interactions ( Lindemann and Schünemann, 2020 ).…”

Visualizing an image network without rendering files: A method to combine user hashtags with computer vision labels

“…The interpretation of the images-hashtags geolocated network should be carried out by mixing social and computational elements. As Marres (2020) indicates, in the study of situations in computational settings, the researcher should consider that social processes happening in digital environments are influenced by the technical specificities of the medium. Therefore, I propose that the methodological strategy schematized in Figure 8 applies to interpreting and situating geolocated Twitter images.…”

Catálogos de video con proceso curatorial basado en datos: republicación de secuencias de video

“…The goal is to have a rich and diverse enough surface for the sampling phase. In the data selection, we aim at diversity in formats (from professional news reports to smartphone videos) and situations (Marres, 2020): tourists strolling in the water, home toilets overflowing with water, a man happily swimming in a flooded Piazza San Marco, boats adrift helplessly trying to reach the dock. The result is 25 videos, for a total running time of roughly 50 minutes (Figure 2).…”