Dino Carpentras

• PhD
• Marie Curie Fellow at University of Limerick

While opinion dynamics models have been extensively studied as stylized models, there has been growing attention to the possibility of combining these models with empirical data. This attention seems to be driven by the many social issues that strongly depend on people's opinions (such as climate change and vaccination) and the need for empirically...

Investigating attitude systems is of key interest to many social scientists. However, “classic” approaches like linear scaling or dimensionality reduction methods risk to hide useful information and may artificially narrow the scope of explanatory theories. As an alternative, scholars have turned to Belief Network Analysis (BNA), which formalizes m...

The social sciences heavily depend on the measurement of abstract constructs for quantifying effects, identifying associations between variables, and testing hypotheses. In data science, constructs are also often used for forecasting, and thanks to the recent big data revolution, they promise to enhance their accuracy by leveraging the constantly i...

The digital revolution, fuelled by advancements in social media, Big Data, the Internet of Things and Artificial Intelligence, is reshaping our urban landscapes into ‘participatory cities’. These cities leverage digital technologies to foster citizen engagement, collaborative decision-making and community-driven urban development, thus unlocking ne...

Currently, there are increasing attempts to better involve citizens in political decision processes. A successful approach in that regard has been participatory budgeting (PB), which allows citizens to propose projects and then decide how to distribute a given budget over them. Meanwhile, the literature on collective intelligence (CI) has also show...

Belief network analysis (BNA) has enabled major advances in the study of belief systems, capturing Converse’s understanding of the interdependence among multiple beliefs (i.e., constraint) more intuitively than conventional statistics. However, BNA models struggle with representing political divisions that follow a spatial logic, such as the “left-...

Decentralized autonomous organizations (DAOs) have transformed organizational structures by shifting from traditional hierarchical control to decentralized approaches, leveraging blockchain and cryptoeconomics. Despite managing significant funds and building global networks, DAOs face challenges like declining participation, increasing centralizati...

Industry 5.0 and Healthcare 5.0 converge towards a human centered society, having technological advancement as a lever. In Society 5.0, decentralized autonomous cities and a convergence of physical and cyberspace are the foundations of the new chapter of society’s development. The idea of creating digital replicas and legitimate representatives of...

Currently, there are increasing attempts to better involve citizens in the political decision processes. A successful approach in that regard has been participatory budgeting (PB), which allows citizens to propose projects and then to decide how to distribute a given budget over them. In the meanwhile, literature on collective intelligence (CI) has...

Belief network analysis (BNA) refers to a class of methods designed to detect and outline structural organizations of complex attitude systems. BNA can be used to analyze attitude-structures of abstract concepts such as ideologies, worldviews, and norm systems that inform how people perceive and navigate the world. The present manuscript presents a...

Analysis of different operationalizations shows that many scientific results may be an artifact of the operationalization process. A culture of multi-operationalization may be needed for psychological research to develop valid knowledge.

Smart societies promise to enhance social systems by leveraging the constantly increasing stream of information around us. However, the possibility of optimizing various social indicators implicitly hinges on our ability to reliably reduce complex and abstract constructs (such as life satisfaction) into numeric measures. While many scientists are a...

We apply a newly developed attitude network-modelling technique (Response-Item Network, or ResIN) to study attitude-identity relationships in the context of hot-button issues that polarize the current US-American electorate. The properties of the network-method allow us to simultaneously depict differences in the structural organization of attitude...

Polarization is a key phenomenon which has been linked to increasing disliking between people of opposite political groups. Furthermore, polarization can extend to new topics such as the debate on COVID-19 vaccines, making it more complex to coordinate efforts for such a problem. The social identity approach (SIA) offers a robust theoretical framew...

Measurements in the social sciences presents numerous problems which are usually not addressed. In this presentation, I discuss where the problems are coming from and all the issues we can face if we neglect the real nature of these measurements (e.g. claim reversal, uncertainty up to 100%, etc.). Finally, I address how we can solve most of these p...

The technological revolution, particularly the availability of more data and more powerful computational tools, has led to the emergence of a new scientific area called Computational Diplomacy. Our work focuses on a popular subarea of it. In recent years, there has been a surge of interest in using digital technologies to promote more participatory...

Agent-based models (ABMs) often rely on psychometric constructs such as ‘opinions’, ‘stubbornness’, ‘happiness’, etc. The measurement process for these constructs is quite different from the one used in physics as there is no standardized unit of measurement for opinion or happiness. Consequently, measurements are usually affected by ‘psychometric...

Opinion dynamics models have an enormous potential for studying current phenomena such as vaccine hesitancy or diffusion of fake news. Unfortunately, to date, most of the models have little to no empirical validation. One major problem in testing these models against real-world data relates to the difficulties in measuring opinions in ways that map...

Vaccines save millions of lives every year. They are recommended by experts, trusted by the majority of people, and promoted by expensive health campaigns. Even so, people with neutral attitudes are more persuaded by people holding anti-vaccine than pro-vaccine attitudes. Our analysis of vaccine-related attitudes in more than 140 countries makes se...

Belief network analysis (BNA) is a new class of methods with strong potential to research the organization and development of abstract meaning systems. By mapping the attitude system, this method provides a more profound understanding of often “fuzzy” concepts such as ideologies, worldviews, and norm systems. BNA therefore holds potential implicati...

The way measurements are defined in the social sciences has a deep impact on modelling, especially on agent-based modelling. In this presentation we show how different measurements of the same construct (e.g. happiness or opinion) can completely alter the measured dynamics (and so the phenomenon to model).

We use a new method based on both network and item response theory to link attitudes to identity. Specifically, we show how our method is able to identify that the American democrats tend to be identified by strongly agreement on some items. While all the other item responses (from weakly agree to strongly disagree) are more related to the republic...

Opinion dynamics models have an enormous potential for studying current phenomena such as vaccine hesitancy. Unfortunately, to date, most of the models have little to no empirical validation. One major problem in testing these models against real-world data relates to the difficulties in measuring opinions in ways that map directly to representatio...

Opinion dynamics models have been developed to study and predict the evolution of public opinion. Intensive research has been carried out on these models, especially exploring the different rules and topologies, which can be considered two degrees of freedom of these models. In this paper we introduce what can be considered a third degree of freedo...

In vivo observation of the human retina at the cellular level is crucial to detect the first signs of retinal diseases and properly treat them. Despite the phenomenal advances in adaptive optics systems, clinical imaging of many retinal cells is still elusive due to the low signal-to-noise ratio induced by transpupillary illumination. We present a...

Opinion dynamics models simulate the evolution of an opinion system by simulating interaction between agents. Most of the models determine the result of each interaction by measuring a distance between the interacting agents. While this concept of distance is clear within the model itself, there is still no consensus on how to measure it from real-...

The in vivo observation of the human retina at the cellular level is crucial to detect lesions before irreversible visual loss occurs, to follow the time course of retinal diseases and to evaluate and monitor the early effects of treatments. Despite the phenomenal advances in optical coherence tomography (OCT) and adaptive optics systems, in vivo i...

Retinal imaging is routinely used to provide information about vision health. Recent studies showed that retinal images can also provide information on general health (e.g. stress level), brain pathologies and attention. Depending on the target information, different imaging systems can be chosen and optimized. This thesis will focus on two distinc...

The observation of retinal cellular structures is fundamental to the understanding of eye pathologies. However, except for rods and cones, most of the retinal microstructures are weakly reflective and thus difficult to image with state of the art reflective optical imaging techniques such as optical coherence tomography. Recently, we demonstrated t...

The evaluation and monitoring of cells health in the human retina is crucial and follow time course of retinal diseases, detect lesions before irreversible visual loss and to evaluate treatment effects. Towards this goal, a major challenge is to image and quantify retinal cells in human eyes in a non-invasive manner. Despite the phenomenal advances...

With the miniaturization of scanning mirrors and the emergence of wearable health monitoring, an intriguing step is to investigate the potential of a laser scanning ophthalmoscope (LSO) for retinal imaging with wearable glasses. In addition to providing morphological information of the retina, such as vasculature, LSO images could also be used to p...

Vision process is ruled by several cells layers of the retina. Before reaching the photoreceptors, light entering the eye has to pass through a few hundreds of micrometers thick layer of ganglion and neurons cells. Macular degeneration is a non-curable disease of themacula occurring with age. This disease can be diagnosed at an early stage by imagi...

The health of cells found in the inner retinal layers of the human eye is crucial to understand the onset of diseases of the retina such as macular degeneration and retinopathy. A challenge is to periodically image these cells in human eyes to detect abnormalities well before physiological and pathological changes occur. However, in vivo imaging of...

The health of cells found in the inner retinal layers of the human eye is crucial to understand the onset of diseases of the retina such as macular degeneration and retinopathy. A challenge is to periodically image these cells in human eyes to detect abnormalities well before physiological and pathological changes occur. However, in vivo imaging of...

In-vivo imaging of the eye’s fundus is widely used to study eye’s health. State of the art Adaptive Optics devices can resolve features up to a lateral resolution of 1.5 um. This resolution is still above what is needed to observe sub-cellular structures such as cone cells (1-1.25 um diameter). This limit in resolution is due to the small numerical...

We present a novel magnetic valving technology designed for lab-on-compact disc (CD) platforms. The working principle is based on a movable plug that, under the effect of the centrifugal force, can close off a channel. The channel can be reopened using magnetic force acting on the plug to lift off the plug from the valve seat. Different geometries...

This thesis presents three novel techniques for valving and a novel method for particle separation for Lab-on-CD (LoCD) technology. All three valving methods are based on the centrifugal force generated by the rotation of the disc and they are also inspired by poppet valves technology. The first one presented in this thesis is a passive magnetic ON...

Quantum Key Distribution together with its intrinsic security represent the more promising technology to meet the challenging requests of novel generation communication protocols. Beyond its relevant commercial interests, QKD is currently and deeply investigated in research fields as quantum information and quantum mechanics foundations, in order t...

In recent years Quantum Key Distribution (QKD) has emerged as the most paradigmatic example of Quantum technology allowing the realization of intrinsically secure communication links over hundreds of kilometers. Beyond its commercial interest QKD also has high conceptual relevance in the study of quantum information theory and the foundations of qu...