Audiovisivi e Social Networks: il testo e i modi dell'esperienza 2007-2010

The doctoral research project "Audiovisuals and Social Networks: Text and Experiences 2007-2010" is mainly based on the analysis of the international audiovisuals landscape and of the promotional strategies of these products in Social Networks environment. The aim is to understand what kind of changes we can find about the concept of "text", users and marketing. The thesis is focused not just on Social Network marketing but also on new media development, such as Social TV and mobile.

Reti socievoli: l’impatto dei social networks nella costruzione dello spazio pubblico

La tesi si è consolidata nell’analisi dell’impatto dei social networks nella costruzione dello spazio pubblico, nella sfera di osservazione che è la rete e il web2.0. Osservando che il paradigma della società civile si sia modificato. Ridefinendo immagini e immaginari e forme di autorappresentazione sui new media (Castells, 2010). Nel presupposto che lo spazio pubblico “non è mai una realtà precostituita” (Innerarity, 2008) ma si muove all’interno di reti che generano e garantiscono socievolezza. Nell’obiettivo di capire cosa è spazio pubblico. Civic engagement che si rafforza in spazi simbolici (Sassen, 2008), nodi d’incontro significativi. Ivi cittadini-consumatori avanzano corresponsabilmente le proprie istanze per la debacle nei governi.. Cultura partecipativa che prende mossa da un nuovo senso civico mediato che si esprime nelle “virtù” del consumo critico. Portando la politica sul mercato. Cultura civica autoattualizzata alla ricerca di soluzioni alle crisi degli ultimi anni. Potere di una comunicazione che riduce il mondo ad un “villaggio globale” e mettono in relazione i pubblici connessi in spazi e tempi differenti, dando origine ad azioni collettive come nel caso degli Indignados, di Occupy Wall Street o di Rai per una notte. Emerge un (ri)pensare la citizenship secondo due paradigmi (Bennett,2008): l’uno orientato al governo attraverso i partiti, modello “Dutiful Citizenship”; l’altro, modello “Self Actualizing Citizenship” per cui i pubblici attivi seguono news ed eventi, percepiscono un minor obbligo nel governo, il voto è meno significativo per (s)fiducia nei media e nei politici. Mercato e società civile si muovono per il bene comune e una nuova “felicità”. La partecipazione si costituisce in consumerismo politico all’interno di reti in cui si sviluppano azioni individuali attraverso il social networking e scelte di consumo responsabile. Partendo dall’etnografia digitale, si è definito il modello “4 C”: Conoscenza > Coadesione > Co-partecipazione > Corresposabilità (azioni collettive) > Cultura-bility.

Networking: the "making of" social networks. A closer look at the process and antecedents of some resourcing-oriented behaviors in organizations.

Social networks are one of the “hot” themes in people’s life and contemporary social research. Considering our “embeddedness” in a thick web of social relations is a study perspective that could unveil a number of explanations of how people may manage their personal and social resources. Looking at people’s behaviors of building and managing their social networks, seems to be an effective way to find some possible rationalization about how to help people getting the best from their resources . The main aim of this dissertation is to give a closer look at the role of networking behaviors. Antecedents, motivations, different steps and measures about networking behaviors and outcomes are analyzed and discussed. Results seem to confirm, in a different setting and time perspective, that networking behaviors include different types and goals that change over time. Effects of networking behaviors seem to find empirical confirmation through social network analysis methods. Both personality and situational self-efficacy seem to predict networking behaviors. Different types of motivational drivers seem to be related to diverse networking behaviors.

Essays on social networks, altruism and information diffusion

This dissertation consists of three standalone articles that contribute to the economics literature concerning technology adoption, information diffusion, and network economics in one way or another, using a couple of primary data sources from Ethiopia. The first empirical paper identifies the main behavioral factors affecting the adoption of brand new (radical) and upgraded (incremental) bioenergy innovations in Ethiopia. The results highlight the importance of targeting different instruments to increase the adoption rate of the two types of innovations. The second and the third empirical papers of this thesis, use primary data collected from 3,693 high school students in Ethiopia, and shed light on how we should select informants to effectively and equitably disseminate new information, mainly concerning environmental issues. There are different well-recognized standard centrality measures that are used to select informants. These standard centrality measures, however, are based on the network topology---shaped only by the number of connections---and fail to incorporate the intrinsic motivations of the informants. This thesis introduces an augmented centrality measure (ACM) by modifying the eigenvector centrality measure through weighting the adjacency matrix with the altruism levels of connected nodes. The results from the two papers suggest that targeting informants based on network position and behavioral attributes ensures more effective and equitable (gender perspective) transmission of information in social networks than selecting informants on network centrality measures alone. Notably, when the information is concerned with environmental issues.

Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.

The Role of B5G UAV-Aided Mobile Networks

With the advent of 5G, several novel network paradigms and technologies have been proposed to fulfil the key requirements imposed. Flexibility, efficiency and scalability, along with sustainability and convenience for expenditure have to be addressed in targeting these brand new needs. Among novel paradigms introduced in the scientific literature in recent years, a constant and increasing interest lies in the use of unmanned aerial vehicles (UAVs) as network nodes supporting the legacy terrestrial network for service provision. Their inherent features of moving nodes make them able to be deployed on-demand in real-time. Which, in practical terms, means having them acting as a base station (BS) when and where there is the highest need. This thesis investigates then the potential role of UAV-aided mobile radio networks, in order to validate the concept of adding an aerial network component and assess the system performance, from early to later stages of its deployment. This study is intended for 5G and beyond systems, to allow time for the technology to mature. Since advantages can be manyfold, the aerial network component is considered at the network layer under several aspects, from connectivity to radio resource management. A particular emphasis is given to trajectory design, because of the efficiency and flexibility it potentially adds to the infrastructure. Two different frameworks have been proposed, to take into account both a re-adaptable heuristic and an optimal solution. Moreover, diverse use cases are taken under analysis, from mobile broadband to machine and vehicular communications. The thesis aim is thus to discuss the potential and advantages of UAV-aided systems from a broad perspective. Results demonstrate that the technology has good prospects for diverse scenarios with a few arrangements.

Self-organising coordination systems

Many research fields are pushing the engineering of large-scale, mobile, and open systems towards the adoption of techniques inspired by self-organisation: pervasive computing, but also distributed artificial intelligence, multi-agent systems, social networks, peer-topeer and grid architectures exploit adaptive techniques to make global system properties emerge in spite of the unpredictability of interactions and behaviour. Such a trend is visible also in coordination models and languages, whenever a coordination infrastructure needs to cope with managing interactions in highly dynamic and unpredictable environments. As a consequence, self-organisation can be regarded as a feasible metaphor to define a radically new conceptual coordination framework. The resulting framework defines a novel coordination paradigm, called self-organising coordination, based on the idea of spreading coordination media over the network, and charge them with services to manage interactions based on local criteria, resulting in the emergence of desired and fruitful global coordination properties of the system. Features like topology, locality, time-reactiveness, and stochastic behaviour play a key role in both the definition of such a conceptual framework and the consequent development of self-organising coordination services. According to this framework, the thesis presents several self-organising coordination techniques developed during the PhD course, mainly concerning data distribution in tuplespace-based coordination systems. Some of these techniques have been also implemented in ReSpecT, a coordination language for tuple spaces, based on logic tuples and reactions to events occurring in a tuple space. In addition, the key role played by simulation and formal verification has been investigated, leading to analysing how automatic verification techniques like probabilistic model checking can be exploited in order to formally prove the emergence of desired behaviours when dealing with coordination approaches based on self-organisation. To this end, a concrete case study is presented and discussed.

Multidimensional analysis of complex networks

Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.

Media activism on and off line by Italian adolescents and young adults

From several researchers it appears that Italian adolescents and young people are grown up with commercial television which is accused to contain too much violence, sex, reality shows, advertising, cartoons which are watched from 1 to 4 hours daily. Adolescents are also great users of mobile phones and spend a lot of time to use it. Their academic results are below the average of Ocse States. However the widespread use of communication technology and social networks display also another side of adolescents who engage in media activism and political movement such as Ammazzateci tutti!, Indymedia, Movimento 5 Stelle, Movimento No Tav. In which way does the world economic crisis -with the specific problems of Italy as the cutting founds for school, academic research and welfare, the corruption of political class, mafia and camorra organisation induce a reaction in our adolescents and young people? Several researches inform us about their use of internet in terms of spending time but, more important, how internet, and the web 2.0, could be an instrument for their reaction? What do they do online? How they do it? Which is the meaning of their presence online? And, has their online activity a continuity offline? The research aims are: 1. Trough a participant observation of Social Network profiles opened by 10 young active citizens, I would seek to understand which kind of social or political activities they engage in online as individuals and which is the meaning of their presence online. 2. To observe and understand if adolescents and young people have a continuity of their socio-political engagement online in offline activities and which kind of experiences it is. 3. Try to comprehend which was (or which were) the significant, learning experiences that convinced them about the potential of the web as tool for their activism.

Normalizzazione del bordello senza muri. L'oscenità virale tra arte, moda e social network

Il progetto di tesi nasce dalla volontà di far luce sul rapporto tra il medium fotografico e la nozione di nuova oscenità, teorizzata e disseminata nei suoi scritti da Jean Baudrillard. Nozione che – se intesa nell’accezione proposta dal filosofo francese, ovvero l’oscenità del visibile, del troppo visibile, del più visibile del visibile – ben si adatta a dettagliare i concetti di trasparenza e di visibilità peculiari della società attuale, costantemente impegnata nel mettere a nudo se stessa attraverso i social media in nome della cosiddetta ideologia della post-privacy. Incoraggiando una continua violazione della sfera del segreto, tale ideologia favorirebbe, infatti, la progressiva diminuzione dello scarto tra ciò che può essere reso di dominio pubblico e ciò che invece, tradizionalmente, sarebbe dovuto appartenere all’ambito del privato. Un andamento generale della cultura, quello appena delineato, che si è imposto capillarmente a cavallo di millennio, accelerato dalla nascita del World Wide Web, del quale la fotografia riesce a farsi promotrice oltre che sommo interprete, contribuendo – anche in virtù di un’innovata condizione tecnologica– al compimento della visibilità e della trasparenza totale. Nel corso della trattazione, la nozione “aggiornata” di osceno sarà, dunque, assurta a strumento euristico utile a tracciare gli svolgimenti paralleli della pratica fotografica nei campi delle arti visive, della moda e dei social media, in un arco temporale che va dall’inizio degli anni Novanta a oggi. Uno strumento attraverso cui connettere autori di riferimento, rileggerne alcuni e candidarne di nuovi tra quanti, allargando il “campo del fotografabile” teorizzato da Pierre Bourdieu, profanano la soglia del privato e portano alla ribalta i risvolti banali e ordinari della quotidianità, fino a quelli intimi, tragici, inquietanti, perturbanti o addirittura nefandi, favorendo così la concretizzazione di quel “bordello senza muri” che secondo Marshall McLuhan è il mondo nell’età fotografica.

Applying machine learning: a multi-role perspective

Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.