1,721,201 research outputs found
Ethnography and the Digital Field: between Text and Context
No full text“Nethnography”, “virtual ethnography”, “cyber-ethnography” and “digital ethnography” are overlapping labels which define a heterogeneous variety of research techniques. They essentially have one thing in common: the digital field. Up to now, the growing literature on online ethnography has not adequately considered the intrinsically dualistic nature of social media. On the one hand, we (both as researchers and users) move throughout a multiplicity of digitally segmented spaces, such as social network profiles, blog posts, forums; on the other hand, we query search engines or explore Twitter’s trends – following topics and issues through keywords. I will suggest that we should distinguish between two types of digital field: a structured, “contextual” field and a fluid, mainly “textual” one – resulting from the aggregation of previously disperse communicative contents. Both these two parallel layers of the online environment influence the users’ digital practices – which now represent a consistent part of people’s everyday life, deeply intertwined with offline social reality. While most of webbased investigations deal with “located” communities, recent studies in the realm of digital ethnography and digital methods tend to focus on “thematic” and “networked” fields instead. This shift recalls Marcus’ appeal for a multi-sited ethnography but, in fact, goes further beyond, towards a truly “un-sited” ethnography. I will highlight the main pros and cons of these two methodological outlooks, also referring to an empirical case study – Erasmus students’ collective identity on Facebook. In the conclusion, I will suggest that the ethnographer’s choice between “text” and “context” depends exclusively on the object investigated
Macchine socializzate e riproduzione tecno-sociale: nuove frontiere sociologiche
No full textCon miliardi di sistemi algoritmici capaci di apprendere stili di classificazione e pratiche culturali, la riproduzione della società diventa inevitabilmente un fatto tecno-sociale. Tuttavia, al tempo di media digitali e machine learning, la sociologia non si è ancora rassegnata al suo destino di disciplina postumana. L’articolo ricostruisce il dibattito intorno allo status delle macchine intelligenti nella teoria sociale e delinea le nuove frontiere sociologiche tracciate dalla loro recente trasformazione in agenti socializzati e socializzanti. Da un lato, gli algoritmi di machine learning acquisiscono disposizioni culturali tramite il confronto con gli universi sociali dataficati di piattaforme e infrastrutture digitali. Dall’altro lato, le disposizioni culturali inscritte nel codice guidano le classificazioni e predizioni automatiche che ordinano invisibilmente il mondo sociale. La tesi dell’articolo è che i meccanismi di riproduzione tecno-sociale debbano diventare un oggetto privilegiato della ricerca sociologica.Social reproduction has become a techno-social fact. However, in the age of digital media and machine learning, sociology has not accepted its inevitable fate of posthuman discipline. This article maps the academic debate on the status of intelligent machines in social theory and outlines the new sociological frontiers resulting from their recent transformation in socialized and socializing agents. On the one side, machine learning algorithms acquire cultural dispositions by confronting with the datafied social universes of platforms and digital infrastructures. On the other side, the cultural dispositions inscribed in the code orient its classifications and automated predictions, which invisibly order the social world. The thesis of the article is that mechanisms of techno-social reproduction must become legitimate objects of sociological research
Machine Habitus: Toward a Sociology of Algorithms
No full textWe commonly think of society as made of and by humans, but with the proliferation of machine learning and AI technologies, this is clearly no longer the case. Billions of automated systems tacitly contribute to the social construction of reality by drawing algorithmic distinctions between the visible and the invisible, the relevant and the irrelevant, the likely and the unlikely – on and beyond platforms.
Drawing on the work of Pierre Bourdieu, this book develops an original sociology of algorithms as social agents, actively participating in social life. Through a wide range of examples, Massimo Airoldi shows how society shapes algorithmic code, and how this culture in the code guides the practical behaviour of the code in the culture, shaping society in turn. The ‘machine habitus’ is the generative mechanism at work throughout myriads of feedback loops linking humans with artificial social agents, in the context of digital infrastructures and pre-digital social structures.
Machine Habitus will be of great interest to students and scholars in sociology, media and cultural studies, science and technology studies and information technology, and to anyone interested in the growing role of algorithms and AI in our social and cultural life
Machine habitus : Sociologia degli algoritmi
No full textOgni giorno miliardi di sistemi automatizzati contribuiscono alla costruzione della società, tracciando distinzioni algoritmiche tra il visibile e l'invisibile, il rilevante e l'irrilevante, il probabile e l'improbabile; le nostre scelte e abitudini generano trame di dati con cui gli algoritmi tessono vite digitali, come abiti su misura. È il machine habitus che riproduce disuguaglianze, plasma comportamenti e opinioni collettive, spesso in modo opaco e con conseguenze imprevedibili. Per comprenderlo serve una sociologia degli algoritmi, proprio come quella delineata da Massimo Airoldi in questo libro
“This is NOT rap” : tastes and reception practices of Italian music listeners on YouTube
No full textMusical taste is a complex thing, being both subjective and collective, intellectual and emotionally-driven, relatively static as well as related to the contexts and activities of the everyday life. This complex picture has become even more fragmented with the diffusion of digital platforms and streaming services, which allow users to browse enormous digital music catalogues at low or no cost, to share their tastes and comment others’, as well as to partly delegate their music choices and discovery to recommender algorithms. YouTube undoubtedly represents one of the main sources for contemporary music lovers. The recent introduction of the “autoplay feature” on the platform, which automatically plays related videos one after the other, makes YouTube users’ experience further algorithmically constructed and it raises new questions about the interplay between music reception and technology. Starting from these premises, this article aims to explore Italian YouTube users’ music taste and reception practices through a mixed methods investigation. More specifically, this study will focus both on the individual use of YouTube as a tool for listening and exploring music and on the social representations of “good” and “bad”, “authentic” and “inauthentic” music emerging from YouTube comments. What is the impact of YouTube, and in particular of its recommendation system, on users’ musical repertoires and reception habits? How does the social construction of musical taste on YouTube comments discursively work? The methods employed for addressing these research questions are, respectively, in-depth qualitative interviews with a theoretical sample of Italian YouTube users and text analysis, conducted on a large corpus of almost 100k comments regarding around 10k Italian popular music videos. The main theoretical goal of this article is not to conceive musical taste simply as an individual feature but as a process, now involving technology as an active and significant component. The main methodological goal relies in the possibility of triangulating the YouTube users’ accounts collected through the interviews with the digital traces of their behaviour on the platform, thus mixing micro and macro, on and offline analyses
The techno-social reproduction of taste boundaries on digital platforms: The case of music on YouTube
No full textRecent research argues that digital platforms contribute to the long-lasting erosion of genre boundaries and established cultural classifications in the “heads and habits” of art consumers (DiMaggio 1987). This paper draws on large volumes of YouTube data to illustrate how, on the contrary, cultural boundaries are techno-socially reproduced online, shedding light on the understudied role of algorithmic systems in the classification of cultural goods. Through a ground-up investigation of how both automated recommendations and the taste patterns of 202,509 platform users segment 14,865 music videos, this work provides empirical evidence of the persistent relevance of categorical boundaries in platformized cultural reception. The recommender system used by YouTube largely relates music videos of the same genre, thus reinforcing pre-existing artistic classifications in the digital circulation of culture. The study also documents how most users do not cross categorical borders in their interactions with musical content, and that boundary strength varies across music genres. I discuss how the interplay between the social patterning of taste and the algorithmic filtering of cultural content generates techno-social feedback loops, and conclude by drawing broad implications for the sociological study of culture and consumption
Lo spettro dell’algoritmo e le scienze sociali. prospettive critiche su macchine intelligenti e automazione delle disuguaglianze [The ghost of the algorithm and the social sciences. Critical perspectives on intelligent machines and the automation of inequalities]
No full textThe last decade has seen a proliferation of journalistic reportages, monographies and academic papers analyzing algorithmic systems and artificial intelligence from a critical perspective. This article reviews four books published in 2018, not yet translated in Italian. They all share the same topic, that is, the socio-political implications of intelligent machines and automating systems. Based on the joint reading of these contributions, The conclusion discusses a series of research directions for a sociology of algorithms. That is: demystifying the code; contextualizing the algorithm; historicizing technology; examining user-machine interactions
Why Sociological Theory Matters in the Age of Algorithms: Considerations on Ori Schwarz’s Sociological Theory for Digital Society
Full text link- …
