Questioning algorithms’ transparency: the case of location based platforms in the context of touristic mobility

In the platform society, algorithms are seen as ‘black boxes’ (Pasquale, 2015) and users have only a vague understanding of the criteria they adopt to select and filter inform ation. Location based platforms' algorithms influence the visibility of different points of interest (POI), thus shaping user interaction with venues and places. This paper will adapt the Diakopoulos and Koliska model (2017), present a new framework for analysing the algorithmic transparency of location based platforms and apply it to three popular location based platforms (Google Maps, Tripadvisor and Instagram) The research questions are the following: RQ1) How do location based platforms communicate algorithmic transparency?; RQ2) Which are the most relevant dimensions they take into consideration (data, model, inference and interface)?; RQ3) How do platforms communicate transparency toward different targets (i.e., consumers and suppliers)? Following Rader, Cotter and Cho (2018), it is expected that location based platforms are less transparent about the data they manage and model they use and slightly more transparent about the inferences (ranking, suggestions and ads). Moreover, we expect location ba sed platforms to be more transparent toward suppliers rather than consumers. This paper will assess how Google Maps, Tripadvisor and Instagram disclose algorithmic transparency as it emerges from the analysis of ‘extant’ online data that has been official ly released (policies, guidelines and tutorials) and from the analysis of the platforms’ mobile The analysis reveals that platforms are less transparent about the data they manage and model they use and more transparent, solely toward supplier s, about the inferences they propose. Moreover, location based platforms are more transparent toward suppliers rather than consumers; indeed, commercial interests favour the algorithmic transparency of location based content.