Modeling narrative features in TV series: coding and clustering analysis

Abstract TV series have gained both economic and cultural relevance. Their development over time can hardly be traced back to the simple programmatic action of creative intentionality. Instead, might studied as narrative ecosystems with emergent trends patterns. This paper aims boost quantitative research in field media studies, first considering a comparative data-driven study features US medical series, one most popular longest-running genres on global television. Based corpus more than 400 h video, we investigate storytelling evolution eight audiovisual serial products by identifying three main (i.e., isotopies). The implemented schematization allows grasp basic components social interactions showing strength genre its ability rebuild, microcosm, essential traits human macrocosm where random everyday life elements (seen cases plot) mix overlap working relationships (professional personal (sentimental plot). relies that combines content analysis clustering analysis. It significantly differs from traditional studies regarding dramas broadly television studies. We proved isotopies are good descriptors for drama identified four profiles which emphasize strong stability these products. Contrary what is often taken granted many interpretative decisions rarely change general aspects wider series.