arXiv subjects

Andrea Guazzini

Publications and source records attributed to Andrea Guazzini.

At least 19 recordsLinked to original sources

arXiv2026

Introducing the Physics of Complex Systems through Videogames

The purpose of this work is to explore a teaching methodology aimed at communicating topics and subjects not typically studied and analyzed in the (Italian) secondary school. We focused specifically on the use of videogames as a recreational and educational tool, grounding our approach in a broadened conceptual view in which engagement and attentional allocation interact with motivational and affective components of play. Within this perspective, the playful format is considered not only to enhance motivation and enjoyment, but also to attenuate learners' counter-arguing tendencies when confronted with unfamiliar or abstract material. Building on this framework, we developed or adapted several videogames whose central scientific topics are phase transitions, sensitivity to initial conditions, and synchronization. We had a certain number of high school students playing the games, and we asked them several questions to guide them and determine whether the communication was successful. At the end of the activity, we administered a questionnaire about the enjoyment and the difficulties encountered in each game, and the relevant critics.

physics.ed-ph↗

arXiv2024

Multiverse of Greatness: Generating Story Branches with LLMs

This paper presents Dynamic Context Prompting/Programming (DCP/P), a novel framework for interacting with LLMs to generate graph-based content with a dynamic context window history. While there is an existing study utilizing LLMs to generate a visual novel game, the previous study involved a manual process of output extraction and did not provide flexibility in generating a longer, coherent story. We evaluate DCP/P against our baseline, which does not provide context history to an LLM and only relies on the initial story data. Through objective evaluation, we show that simply providing the LLM with a summary leads to a subpar story compared to additionally providing the LLM with the proper context of the story. We also provide an extensive qualitative analysis and discussion. We qualitatively examine the quality of the objectively best-performing generated game from each approach. In addition, we examine biases in word choices and word sentiment of the generated content. We find a consistent observation with previous studies that LLMs are biased towards certain words, even with a different LLM family. Finally, we provide a comprehensive discussion on opportunities for future studies.

cs.CL↗

arXiv2019

Humans make best use of social heuristics when confronting hard problems in large groups

We report the results of a game-theoretic experiment with human players who solve the problems of increasing complexity by cooperating in groups of increasing size. Our experimental environment is set up to make it complicated for players to use rational calculation for making the cooperative decisions. This environment is directly translated into a computer simulation, from which we extract the collaboration strategy that leads to the maximal attainable score. Based on this, we measure the error that players make when estimating the benefits of collaboration, and find that humans massively underestimate these benefits when facing easy problems or working alone or in small groups. In contrast, when confronting hard problems or collaborating in large groups, humans accurately judge the best level of collaboration and easily achieve the maximal score. Our findings are independent on groups' composition and players' personal traits. We interpret them as varying degrees of usefulness of social heuristics, which seems to depend on the size of the involved group and the complexity of the situation.

physics.soc-ph↗

arXiv2017

The Peace Mediator effect: Heterogeneous agents can foster consensus in continuous opinion models

Statistical mechanics has proven to be able to capture the fundamental rules underlying phenomena of social aggregation and opinion dynamics, well studied in disciplines like sociology and psychology. This approach is based on the underlying paradigm that the interesting dynamics of multi-agent systems emerge from the correct definition of few parameters governing the evolution of each individual. Into this context, we propose a particular model of opinion dynamics based on the psychological construct named "cognitive dissonance". Our system is made of interacting individuals, the agents, each bearing only two dynamical variables (respectively "opinion" and "affinity") self-consistently adjusted during time evolution. We also define two special classes of interacting entities, both acting for a peace mediation process but via different course of action: "diplomats" and "auctoritates". The behavior of the system with and without peace mediators (PMs) is investigated and discussed with reference to corresponding psychological and social implications.

physics.soc-ph↗

arXiv2016

Stochastic Agent-Based Models of Intimate Partner Violence

Intimate partner violence (IPV) is a significant public health problem and social issue that involves couples from all socioeconomic and cultural contexts. IPV may affect women and men, but these latter are the most common perpetrators of IPV. We developed stochastic Agent-Based models of IPV focused on the couple dynamics, determined by the parallel, individual behaviour of partners. Based on the psychological theory of the Cycle of Violence, we have developed a model based on four discrete states: passivity, normal situation, upset and physical assault. The individual transition probability depends on the previous state of the subject and that of the partner, and on a control parameter, the aggressiveness. We then let this parameter evolve depending on the perceived violence from past experiences (polarisation) or from the support received from the environment (social influence). From the analysis of the phase diagrams we observe the emergence of characteristic patterns, in agreement with the observations of IPV in the literature.

cs.SI↗

arXiv2016

Collective Intelligence Heuristic: An Experimental Evidence

The main intreest of this study was to investigate the phenomenon of collective intelligence in an anonymous virtual environment developed for this purpose. In particular, we were interested in studiyng how dividing a fixed community in different group size, which, in different phases of the experiment, works to solve tasks of different complexity, influences the social problem solving process. The experiments, which have involved 216 university students, showed that the cooperative behaviour is stronger in small groups facing complex tasks: the cooperation probability negatively correlated with both the group size and easiness of task. Individuals seem to activate a collective intelligence heuristics when the problem is too complex. Some psychosocial variables were considered in order to check how they affect the cooperative behaviour of participants, but they do not seem to have a significant impact on individual cooperation probability, supporting the idea that a partial de-individualization operates in virtual environments.

cs.SI↗

arXiv2016

Non-trivial reputation effects on social decision making in virtual environment

Reputation systems are currently used, often with success, to ensure the functioning of online services as well as of e-commerce sites. Despite the relationship between reputation and material cooperative behaviours is quite supported, less obvious appears the relationship with informative behaviours, which are crucial for the transmission of reputational information and therefore for the maintenance of cooperation among individuals. The purpose of this study was to verify how reputation affects cooperation dynamics in virtual environment, within a social dilemma situation (i.e., where there are incentives to act selfishly). The results confirm that reputation can activate prosocial conducts, however it highlights also the limitations and distortions that reputation can create.

cs.SI↗

arXiv2016

Conformity in virtual environments: a hybrid neurophysiological and psychosocial approach

The main aim of our study was to analyse the effects of a virtual environment on social conformity, with particular attention to the effects of different types of task and psychological variables on social influence, on one side, and to the neural correlates related to conformity, measured by means of an Emotiv EPOC device on the other. For our purpose, we replicated the famous Asch's visual task and created two new tasks of increasing ambiguity, assessed through the calculation of the item's entropy. We also administered five scales in order to assess different psychological traits. From the experiment, conducted on 181 university students, emerged that conformity grows according to the ambiguity of the task, but normative influence is significantly weaker in virtual environments, if compared to face-to-face experiments. The analysed psycho-logical traits, however, result not to be relatable to conformity, and they only affect the subjects' response times. From the ERP (Event-related potentials) analysis, we detected N200 and P300 components comparing the plots of conformist and non-conformist subjects, alongside with the detection of their Late Positive Potential, Readiness Potential, and Error-Related Negativity, which appear consistently different for the two typologies.

cs.HC↗

arXiv2016

Self-presentation and emotional contagion on Facebook: new experimental measures of profiles' emotional coherence

Social Networks allow users to self-present by sharing personal contents with others which may add comments. Recent studies highlighted how the emotions expressed in a post affect others' posts, eliciting a congruent emotion. So far, no studies have yet investigated the emotional coherence between wall posts and its comments. This research evaluated posts and comments mood of Facebook profiles, analyzing their linguistic features, and a measure to assess an excessive self-presentation was introduced. Two new experimental measures were built, describing the emotional loading (positive and negative) of posts and comments, and the mood correspondence between them was evaluated. The profiles "empathy", the mood coherence between post and comments, was used to investigate the relation between an excessive self-presentation and the emotional coherence of a profile. Participants publish a higher average number of posts with positive mood. To publish an emotional post corresponds to get more likes, comments and receive a coherent mood of comments, confirming the emotional contagion effect reported in literature. Finally, the more empathetic profiles are characterized by an excessive self-presentation, having more posts, and receiving more comments and likes. To publish emotional contents appears to be functional to receive more comments and likes, fulfilling needs of attention-seeking.

cs.SI↗

arXiv2016

Participation and Privacy perception in virtual environments: the role of sense of community, culture and sex between Italian and Turkish

Advancements in information and communication technologies have enhanced our possibilities to communicate worldwide, eliminating borders and making it possible to interact with people coming from other cultures like never happened before. Such powerful tools have brought us to reconsider our concept of privacy and social involvement in order to make them fit into this wider environment. It is possible to claim that the ICT revolution is changing our world and is having a core role as a mediating factor for social movements (e.g., Arab spring) and political decisions (e.g., Brexit), shaping the world in a faster and shared brand new way. It is then interesting to explore how the perception of this brand new environment (in terms of social engagement, privacy perception and sense of belonging to a community) differs even in similar cultures separated by recent historical reasons, as for example in Italian and Turkish cultures.

cs.CY↗

arXiv2016

Modeling crowdsourcing as collective problem solving

Crowdsourcing is a process of accumulating the ideas, thoughts or information from many independent participants, with aim to find the best solution for a given challenge. Modern information technologies allow for massive number of subjects to be involved in a more or less spontaneous way. Still, the full potentials of crowdsourcing are yet to be reached. We introduce a modeling framework through which we study the effectiveness of crowdsourcing in relation to the level of collectivism in facing the problem. Our findings reveal an intricate relationship between the number of participants and the difficulty of the problem, indicating the optimal size of the crowdsourced group. We discuss our results in the context of modern utilization of crowdsourcing.

physics.soc-ph↗

arXiv2016

The Peace Mediator Effect

Statistical mechanics has proven to be able to capture the fundamental rules underlying phenomena of social aggregation and opinion dynamics, well studied in disciplines like sociology and psychology. This approach is based on the underlying paradigm that the interesting dynamics of multi-agent systems emerge from the correct definition of few parameters governing the evolution of each individual. Into this context, we propose a new model of opinion dynamics based on the psychological construct named "cognitive dissonance". Our system is made of interacting individuals, the agents, each bearing only two dynamical variables (respectively "opinion" and "affinity") self-consistently adjusted during time evolution. We also define two special classes of interacting entities, both acting for a peace mediation process but via different course of action: "diplomats" and "auctoritates". The behaviour of the system with and without peace mediators (PMs) is investigated and discussed with reference to corresponding psychological and social implications.

physics.soc-ph↗

arXiv2013

Impact of local information in growing networks

We present a new model of the evolutionary dynamics and the growth of on-line social networks. The model emulates people's strategies for acquiring information in social networks, emphasising the local subjective view of an individual and what kind of information the individual can acquire when arriving in a new social context. The model proceeds through two phases: (a) a discovery phase, in which the individual becomes aware of the surrounding world and (b) an elaboration phase, in which the individual elaborates locally the information trough a cognitive-inspired algorithm. Model generated networks reproduce main features of both theoretical and real-world networks, such as high clustering coefficient, low characteristic path length, strong division in communities, and variability of degree distributions.

cs.SI↗

arXiv2013

Application of a cognitive-inspired algorithm for detecting communities in mobility networks

The emergence and the global adaptation of mobile devices has influenced human interactions at the individual, community, and social levels leading to the so called Cyber-Physical World (CPW) convergence scenario [1]. One of the most important features of CPW is the possibility of exploiting information about the structure of the social communities of users, revealed by joint movement patterns and frequency of physical co-location. Mobile devices of users that belong to the same social community are likely to "see" each other (and thus be able to communicate through ad-hoc networking techniques) more frequently and regularly than devices outside the community. In mobile opportunistic networks, this fact can be exploited, for example, to optimize networking operations such as forwarding and dissemination of messages. In this paper we present the application of a cognitive-inspired algorithm [2,3,4] for revealing the structure of these dynamic social networks (simulated by the HCMM model [5]) using information about physical encounters logged by the users' mobile devices. The main features of our algorithm are: (i) the capacity of detecting social communities induced by physical co-location of users through distributed algorithms; (ii) the capacity to detect users belonging to more communities (thus acting as bridges across them), and (iii) the capacity to detect the time evolution of communities.

physics.soc-ph↗

arXiv2012

Modeling Risk Perception in Networks with Community Structure

We study the influence of global, local and community-level risk perception on the extinction probability of a disease in several models of social networks. In particular, we study the infection progression as a susceptible-infected-susceptible (SIS) model on several modular networks, formed by a certain number of random and scale-free communities. We find that in the scale-free networks the progression is faster than in random ones with the same average connectivity degree. For what concerns the role of perception, we find that the knowledge of the infection level in one's own neighborhood is the most effective property in stopping the spreading of a disease, but at the same time the more expensive one in terms of the quantity of required information, thus the cost/effectiveness optimum is a tradeoff between several parameters.

physics.soc-ph↗

arXiv2012

A cognitive-inspired model for self-organizing networks

In this work we propose a computational scheme inspired by the workings of human cognition. We embed some fundamental aspects of the human cognitive system into this scheme in order to obtain a minimization of computational resources and the evolution of a dynamic knowledge network over time, and apply it to computer networks. Such algorithm is capable of generating suitable strategies to explore huge graphs like the Internet that are too large and too dynamic to be ever perfectly known. The developed algorithm equips each node with a local information about possible hubs which are present in its environment. Such information can be used by a node to change its connections whenever its fitness is not satisfying some given requirements. Eventually, we compare our algorithm with a randomized approach within an ecological scenario for the ICT domain, where a network of nodes carries a certain set of objects, and each node retrieves a subset at a certain time, constrained with limited resources in terms of energy and bandwidth. We show that a cognitive-inspired approach improves the overall networks topology better than a randomized algorithm.

physics.soc-ph↗

arXiv2012

Cognitive network structure: an experimental study

In this paper we present first experimental results about a small group of people exchanging private and public messages in a virtual community. Our goal is the study of the cognitive network that emerges during a chat seance. We used the Derrida coefficient and the triangle structure under the working assumption that moods and perceived mutual affinity can produce results complementary to a full semantic analysis. The most outstanding outcome is the difference between the network obtained considering publicly exchanged messages and the one considering only privately exchanged messages: in the former case, the network is very homogeneous, in the sense that each individual interacts in the same way with all the participants, whilst in the latter the interactions among different agents are very heterogeneous, and are based on "the enemy of my enemy is my friend" strategy. Finally a recent characterization of the triangular cliques has been considered in order to describe the intimate structure of the network. Experimental results confirm recent theoretical studies indicating that certain 3-vertex structures can be used as indicators for the network aging and some relevant dynamical features.

physics.soc-ph↗

arXiv2012

Community-detection cellular automata with local and long-range connectivity

We explore a community-detection cellular automata algorithm inspired by human heuristics, based on information diffusion and a non-linear processing phase with a dynamics inspired by human heuristics. The main point of the methods is that of furnishing different "views" of the clustering levels from an individual point of view. We apply the method to networks with local connectivity and long-range rewiring.

nlin.CG↗