Cristel Kolopaking | Re-Frame: Tracing Re-Use of Audiovisual Data in Journalism | Overarching project: RE-FRAME (CLICK-NL) with cooperating institutes: Netherlands Institute for Sound and Vision; Make Media Great Again | Utrecht University, Mediastudies | Promotor(es); supervisor(s): Prof. dr. José van Dijck, prof. Tamara Witschge and dr. Jasmijn van Gorp | 01 April 2021 – 30 March 2025 | c.a.kolopaking[at]uu.nl
Cristel Kolopaking is a PhD candidate at the Institute for Cultural Inquiry in the RE-FRAME project, based on a collaboration between Utrecht University, the Netherlands Institute for Sound and Vision and Make Media Great Again. RE-FRAME addresses the merging of journalistic sourcing practices by investigating the reuse of audiovisual data with Artificial Intelligence (AI) through an affordance analysis of the technical components, combined with an ethnographic production and action-based research with journalists. More specifically, this investigation focuses on the role of concrete AI techniques like Automatic Speech Recognition (ASR) and Computer Vision (CV) in the search and selection process of audiovisual data within the NISV Media Suite as part of journalistic production processes. ASR allows spoken text within audiovisual media to be transcribed and hence searched for specific queries across audiovisual data. CV enables the recognition of objects, faces, colours, locations and movements across audiovisual data. Both AI techniques can thus automatically generate forms of metadata that go beyond archival metadata (Wevers and Smits 2020). By utilizing these techniques new patterns can beexplored across audiovisual data and hence different frames can be reused for journalistic productions. By studying this process through several empirical parts consisting of an affordance analysis, content analysis, interviews and action-based production analysis with journalists, this project will gain insights into the following research question:
How are sources and specific audiovisual data re-used and potentially framed within journalistic productions and what role do AI techniques such as ASR and CV play within this search, selection, interpretation and publication process from a critical tool- and data perspective?