Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.

Mainstreaming of Nature-Based Solutions for the mitigation of hydro-meteorological hazard: governance analysis of a socio- technical change

The Nature-Based Solutions (NBS) concept and approach were developed to simultaneously face challenges such as risk mitigation and biodiversity conservation and restoration. NBSs have been endorsed by major International Organizations such as the EU, the FAO and World Bank that are pushing to enable a mainstreaming process. However, a shift from traditional engineering “grey” solutions to wider and standard adoption of NBS encounters technical, social, cultural, and normative barriers that have been identified with a qualitative content analysis of policy documents, reports and expert interviews. The case of the region Emilia-Romagna was studied by developing an analytical framework that brought together the social-ecological context, the governance system and the characteristics of specific NBSs.

Filiera corta: percorsi di innovazione tecnici, organizzativi e sociali nella gestione strategica delle nicchie. Esperienze in Toscana e in Provenza

There is a widening consensus around the fact that, in many developed countries, food production-consumption patterns are in recent years interested by a process of deep change towards diversification and re-localisation practices, as a counter-tendency to the trend to the increasing disconnection between farming and food, producers and consumers. The relevance of these initiatives doesn't certainly lie on their economic dimension, but rather in their intense diffusion and growth rate, their spontaneous and autonomous nature and, especially, their intrinsic innovative potential. These dynamics involve a wide range of actors around local food patterns, embedding short food supply chains initiatives within a more complex and wider process of rural development, based on principles of sustainability, multifunctionality and valorisation of endogenous resources. In this work we have been analysing these features through a multi-level perspective, with reference to the dynamics between niche and regime and the inherent characteristics of the innovation paths. We apply this approach, through a qualitative methodology, to the analysis of the experience of farmers’ markets and Solidarity-Based Consumers Groups (Gruppi di Acquisto Solidale) ongoing in Tuscany, seeking to highlight the dynamics that are affecting the establishment of this alternative food production-consumption model (and its related innovative potential) from within and from without. To verify if and in which conditions they can constitute a niche, a protected space where radical innovations can develop, we make reference to the three interrelated analytic dimensions of socio-technical systems: the actors (i.e. individuals. social groups, organisations), the rules and institutions system, and the artefacts (i.e. the material and immaterial contexts in which the actors move). Through it, we analyse the innovative potential of niches and the level of their structuration and , then, the mechanisms of system transition, focusing on the new dynamics within the niche and between the niche and the policy regime emerging after the growth of interest by mass-media and public institutions and their direct involvement in the initiatives. Following the development of these significant experiences, we explore more deeply social, economic, cultural, political and organisational factors affecting innovations in face-to-face interactions, underpinning the critical aspects (sharing of alternative values, coherence at individual choices level, frictions on organisational aspects, inclusion/exclusion, attitudes towards integration at territorial level), towards uncovering until to the emergence of tensions and the risks of opportunistic behaviours that might arise from their growth. Finally, a comparison with similar experiences abroad is drawn (specifically with Provence), in order to detect food for thought, potentially useful for leading regional initiativestowards transition path.

Algorithmic business and EU law on fair trading

This thesis studies how commercial practice is developing with artificial intelligence (AI) technologies and discusses some normative concepts in EU consumer law. The author analyses the phenomenon of 'algorithmic business', which defines the increasing use of data-driven AI in marketing organisations for the optimisation of a range of consumer-related tasks. The phenomenon is orienting business-consumer relations towards some general trends that influence power and behaviors of consumers. These developments are not taking place in a legal vacuum, but against the background of a normative system aimed at maintaining fairness and balance in market transactions. The author assesses current developments in commercial practices in the context of EU consumer law, which is specifically aimed at regulating commercial practices. The analysis is critical by design and without neglecting concrete practices tries to look at the big picture. The thesis consists of nine chapters divided in three thematic parts. The first part discusses the deployment of AI in marketing organisations, a brief history, the technical foundations, and their modes of integration in business organisations. In the second part, a selected number of socio-technical developments in commercial practice are analysed. The following are addressed: the monitoring and analysis of consumers’ behaviour based on data; the personalisation of commercial offers and customer experience; the use of information on consumers’ psychology and emotions, the mediation through marketing conversational applications. The third part assesses these developments in the context of EU consumer law and of the broader policy debate concerning consumer protection in the algorithmic society. In particular, two normative concepts underlying the EU fairness standard are analysed: manipulation, as a substantive regulatory standard that limits commercial behaviours in order to protect consumers’ informed and free choices and vulnerability, as a concept of social policy that portrays people who are more exposed to marketing practices.

Embedded representations of social interactions

Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.

Investing for impact. An exploration of impact investments in rural Ghana

This thesis offers an exploration of impact and social investments for agricultural development projects in Sub-Saharan Africa. It does so through the case of SustAgric-Africa (SAA), a social enterprise that aims to lift smallholder farmers out of poverty through the promotion of sustainable farming and operates with capital provided by a variety of investors who are committed to pairing financial returns with social and environmental outcomes. The thesis sets off to answer the following research questions: What is the moral dimension that emerges in finance with the establishment of environmental and social criteria? What kind of arrangements do social and impact investments give origin to? Is it possible to talk about a ‘spirit of the gift’ in such arrangements? What happens when abstract and globalizing ideas around ‘impact’ hit the ground? Drawing from the STS and Actor-Network Theory, I look at the formation engendered by social and impact investments in terms of a socio-technical arrangement, and look at the movements of “objects” between the main actors in terms of circuits. In these processes ideas about ‘value’ and ‘values’ articulate in complex ways in the interplay of gift, debt and credit in the relationships among the three main categories of involved actors: investors, SAA, and the farmers. In the case of SAA, I contend that the ways abstract and globalising ideas about ‘impact’ hit the ground produce uncertain results and contribute to the reproduction of inequalities and unequal wealth distribution and accumulation, deepening ongoing processes of financialization. However, my ethnography also reveals how actors depicted as beneficiaries of impact and social policies and resources, far from being passive recipients of policies and resources, actually question and appropriate them, potentially unsettling the whole arrangement and the moral and ethical claims underpinning it.

Distributed ledger technologies between anonymity and transparency: AML/CFT regulation of cryptocurrency ecosystems in the EU

The advent of Bitcoin suggested a disintermediated economy in which Internet users can take part directly. The conceptual disruption brought about by this Internet of Money (IoM) mirrors the cross-industry impacts of blockchain and distributed ledger technologies (DLTs). While related instances of non-centralisation thwart regulatory efforts to establish accountability, in the financial domain further challenges arise from the presence in the IoM of two seemingly opposing traits: anonymity and transparency. Indeed, DLTs are often described as architecturally transparent, but the perceived level of anonymity of cryptocurrency transfers fuels fears of illicit exploitation. This is a primary concern for the framework to prevent money laundering and the financing of terrorism and proliferation (AML/CFT/CPF), and a top priority both globally and at the EU level. Nevertheless, the anonymous and transparent features of the IoM are far from clear-cut, and the same is true for its levels of disintermediation and non-centralisation. Almost fifteen years after the first Bitcoin transaction, the IoM today comprises a diverse set of socio-technical ecosystems. Building on an analysis of their phenomenology, this dissertation shows how there is more to their traits of anonymity and transparency than it may seem, and how these features range across a spectrum of combinations and degrees. In this context, trade-offs can be evaluated by referring to techno-legal benchmarks, established through socio-technical assessments grounded on teleological interpretation. Against this backdrop, this work provides framework-level recommendations for the EU to respond to the twofold nature of the IoM legitimately and effectively. The methodology cherishes the mutual interaction between regulation and technology when drafting regulation whose compliance can be eased by design. This approach mitigates the risk of overfitting in a fast-changing environment, while acknowledging specificities in compliance with the risk-based approach that sits at the core of the AML/CFT/CPF regime.

Mind the gaps: cognitive-inspired AI for high-level visual sensemaking. Towards abstract concept image classification

The abundance of visual data and the push for robust AI are driving the need for automated visual sensemaking. Computer Vision (CV) faces growing demand for models that can discern not only what images "represent," but also what they "evoke." This is a demand for tools mimicking human perception at a high semantic level, categorizing images based on concepts like freedom, danger, or safety. However, automating this process is challenging due to entropy, scarcity, subjectivity, and ethical considerations. These challenges not only impact performance but also underscore the critical need for interoperability. This dissertation focuses on abstract concept-based (AC) image classification, guided by three technical principles: situated grounding, performance enhancement, and interpretability. We introduce ART-stract, a novel dataset of cultural images annotated with ACs, serving as the foundation for a series of experiments across four key domains: assessing the effectiveness of the end-to-end DL paradigm, exploring cognitive-inspired semantic intermediaries, incorporating cultural and commonsense aspects, and neuro-symbolic integration of sensory-perceptual data with cognitive-based knowledge. Our results demonstrate that integrating CV approaches with semantic technologies yields methods that surpass the current state of the art in AC image classification, outperforming the end-to-end deep vision paradigm. The results emphasize the role semantic technologies can play in developing both effective and interpretable systems, through the capturing, situating, and reasoning over knowledge related to visual data. Furthermore, this dissertation explores the complex interplay between technical and socio-technical factors. By merging technical expertise with an understanding of human and societal aspects, we advocate for responsible labeling and training practices in visual media. These insights and techniques not only advance efforts in CV and explainable artificial intelligence but also propel us toward an era of AI development that harmonizes technical prowess with deep awareness of its human and societal implications.

Creazione e sviluppo di corpora multimediali. Nuove metodologie di ricerca nella traduzione audiovisiva

The construction and use of multimedia corpora has been advocated for a while in the literature as one of the expected future application fields of Corpus Linguistics. This research project represents a pioneering experience aimed at applying a data-driven methodology to the study of the field of AVT, similarly to what has been done in the last few decades in the macro-field of Translation Studies. This research was based on the experience of Forlixt 1, the Forlì Corpus of Screen Translation, developed at the University of Bologna’s Department of Interdisciplinary Studies in Translation, Languages and Culture. As a matter of fact, in order to quantify strategies of linguistic transfer of an AV product, we need to take into consideration not only the linguistic aspect of such a product but all the meaning-making resources deployed in the filmic text. Provided that one major benefit of Forlixt 1 is the combination of audiovisual and textual data, this corpus allows the user to access primary data for scientific investigation, and thus no longer rely on pre-processed material such as traditional annotated transcriptions. Based on this rationale, the first chapter of the thesis sets out to illustrate the state of the art of research in the disciplinary fields involved. The primary objective was to underline the main repercussions on multimedia texts resulting from the interaction of a double support, audio and video, and, accordingly, on procedures, means, and methods adopted in their translation. By drawing on previous research in semiotics and film studies, the relevant codes at work in visual and acoustic channels were outlined. Subsequently, we concentrated on the analysis of the verbal component and on the peculiar characteristics of filmic orality as opposed to spontaneous dialogic production. In the second part, an overview of the main AVT modalities was presented (dubbing, voice-over, interlinguistic and intra-linguistic subtitling, audio-description, etc.) in order to define the different technologies, processes and professional qualifications that this umbrella term presently includes. The second chapter focuses diachronically on various theories’ contribution to the application of Corpus Linguistics’ methods and tools to the field of Translation Studies (i.e. Descriptive Translation Studies, Polysystem Theory). In particular, we discussed how the use of corpora can favourably help reduce the gap existing between qualitative and quantitative approaches. Subsequently, we reviewed the tools traditionally employed by Corpus Linguistics in regard to the construction of traditional “written language” corpora, to assess whether and how they can be adapted to meet the needs of multimedia corpora. In particular, we reviewed existing speech and spoken corpora, as well as multimedia corpora specifically designed to investigate Translation. The third chapter reviews Forlixt 1's main developing steps, from a technical (IT design principles, data query functions) and methodological point of view, by laying down extensive scientific foundations for the annotation methods adopted, which presently encompass categories of pragmatic, sociolinguistic, linguacultural and semiotic nature. Finally, we described the main query tools (free search, guided search, advanced search and combined search) and the main intended uses of the database in a pedagogical perspective. The fourth chapter lists specific compilation criteria retained, as well as statistics of the two sub-corpora, by presenting data broken down by language pair (French-Italian and German-Italian) and genre (cinema’s comedies, television’s soapoperas and crime series). Next, we concentrated on the discussion of the results obtained from the analysis of summary tables reporting the frequency of categories applied to the French-Italian sub-corpus. The detailed observation of the distribution of categories identified in the original and dubbed corpus allowed us to empirically confirm some of the theories put forward in the literature and notably concerning the nature of the filmic text, the dubbing process and Italian dubbed language’s features. This was possible by looking into some of the most problematic aspects, like the rendering of socio-linguistic variation. The corpus equally allowed us to consider so far neglected aspects, such as pragmatic, prosodic, kinetic, facial, and semiotic elements, and their combination. At the end of this first exploration, some specific observations concerning possible macrotranslation trends were made for each type of sub-genre considered (cinematic and TV genre). On the grounds of this first quantitative investigation, the fifth chapter intended to further examine data, by applying ad hoc models of analysis. Given the virtually infinite number of combinations of categories adopted, and of the latter with searchable textual units, three possible qualitative and quantitative methods were designed, each of which was to concentrate on a particular translation dimension of the filmic text. The first one was the cultural dimension, which specifically focused on the rendering of selected cultural references and on the investigation of recurrent translation choices and strategies justified on the basis of the occurrence of specific clusters of categories. The second analysis was conducted on the linguistic dimension by exploring the occurrence of phrasal verbs in the Italian dubbed corpus and by ascertaining the influence on the adoption of related translation strategies of possible semiotic traits, such as gestures and facial expressions. Finally, the main aim of the third study was to verify whether, under which circumstances, and through which modality, graphic and iconic elements were translated into Italian from an original corpus of both German and French films. After having reviewed the main translation techniques at work, an exhaustive account of possible causes for their non-translation was equally provided. By way of conclusion, the discussion of results obtained from the distribution of annotation categories on the French-Italian corpus, as well as the application of specific models of analysis allowed us to underline possible advantages and drawbacks related to the adoption of a corpus-based approach to AVT studies. Even though possible updating and improvement were proposed in order to help solve some of the problems identified, it is argued that the added value of Forlixt 1 lies ultimately in having created a valuable instrument, allowing to carry out empirically-sound contrastive studies that may be usefully replicated on different language pairs and several types of multimedia texts. Furthermore, multimedia corpora can also play a crucial role in L2 and translation teaching, two disciplines in which their use still lacks systematic investigation.