Titolo della tesi: TikTok as Television. Navigating Algorithmic Entertainment in the Platform Era
Consuming audiovisual media is becoming an increasingly complex activity: what was once limited to the cinema, and later the television screen, has now become a pervasive presence on all digital platforms. The ecosystem of entertainment platforms is deeply intricate, and the boundaries between user-generated content and professionally produced content are slowly fading, paving the way for hybrid video formats to emerge and populate media sharing platforms (as well as SVOD services). The goal of this dissertation is to frame TikTok within this media ecosystem, finding an adequate classification for the platform, and understanding the impact that its recommendation algorithm has on people’s use of the app.
This will be done by initially focusing on the concept of flow, introduced by Raymond Williams in 1974. The focus will be twofold. On the one hand, it will be analysed in the context of traditional linear television, looking at the paradigm shifts within the medium (from broadcasting to narrowcasting, and then to personcasting) and the establishment of timeshifting and placeshifting practices, which lead to the necessity to redefine flow experiences (van Dijck, 2013b; Cox, 2018), as well as the concept of liveness (Gemini, Brilli 2023; Couldry, 2005) which has always been associated with them.
On the other hand, the concept of flow will be considered alongside the impact that recommendation algorithms have had on users’ consumption habits. Throughout the dissertation, algorithms will be framed as actors (Latour, 2005), and their impact will be analysed both on traditionally televisual (Caldwell, 1995) platforms and media sharing platforms. This analysis will be instrumental in the introduction of a new paradigm shift towards datacasting: what is placed at the centre here is the role that data plays during the suggestion and selection processes when it comes to audiovisual content. The flow becomes algorithmic, linear but determined by algorithmic suggestions rather than by a broadcaster’s editorial control.
Within this multifaceted environment TikTok has managed to affirm itself as one of the most popular platforms globally, and the most popular “social media platform” in Italy, according to We Are Social’s “Digital 2024” report. The platform is typically associated to other social media platforms, however, one of the main elements of the platform is its algorithmic flow which, following Uricchio (2004), would make it a televisual platform. The questions this dissertation aims to answer are: RQ1 What do TikTok users use the platform for?; RQ2 Does a televisual categorisation of the platform emerge from user discourses surrounding the app? What impact does the algorithmic flow have on their experiences of the platform?; RQ3 Does a level of algorithmic awareness emerge from user discourses surrounding the app? What impact does this level have on their interactions with the platform?
To best gather data on the subject, and to ensure that people had space to express their feelings and opinions, 30 semi-structured interviews were carried out following a grounded theory approach (Hutchinson, Skodol Wilson, 2001; Glaser, Strauss, 1967) with TikTok users aged 18-34. Ultimately, the analysis served two main purposes: the first was to develop the framework of affective domestication, a reformulation of the domestication process (Silverstone, Hirsch, Morley, 1992) that takes into account the role that human emotion plays in shaping an algorithmic system that is programmed to suggest (audiovisual) content. The second was to frame TikTok as a televisual platform, based on people’s experiences and their interpretation of the platform, focusing on the role it plays within their everyday routines.