Work Packages
The ALGOFEED project develops through a sequential mixed-methods research design, which articulates in three (interconnected) work packages (WPs).
WP1 – Short pre-tracking survey. This WP aims at analysing the joint evolution of individual cultural consumption trajectories and personalised algorithmic recommendations over time. To do that, a quota sample of 240 active Italian users of both YouTube and TikTok, aged 18 to 40 years old, will be recruited and a short online questionnaire will be administered. The scope of the questionnaire is to profile participants based on their digital skills and platformed-based consumption habits.
WP2 – Longitudinal digital tracking. This WP aims at understanding the cultural consequences of aggregate content recommendation trends at the platform level over time. To do that, a longitudinal and cross-platform tracking of cultural content recommendations proposed by YouTube and TikTok to each of the 240 participants recruited in WP1 will be performed – (over a period of 3 months). The scope of the longitudinal digital tracking is to: a) classify the recommended cultural content based on relevant metadata (e.g., timestamps, keywords, etc.); and b) map significant micro and macro variations in participants’ practices of content consumption over time. Data will be analysed through ad hoc digital and computational techniques.
WP3 – Qualitative follow-up interviews. This WP aims at exploring consumers’ awareness and understandings of platform-based recommendation systems. To do that, in-depth qualitative interviews with a subsample of 40 participants recruited in WP2 will be conducted. The scope of the interviews is to; a) investigate how consumers understand recommendation systems and their socio-cultural effects; and b) expand the awareness of participants about the existence and implications of recommender algorithms.