8,967 research outputs found
Attributed Stream Hypergraphs: temporal modeling of node-attributed high-order interactions
No full textAbstract Recent advances in network science have resulted in two distinct research directions aimed at augmenting and enhancing representations for complex networks. The first direction, that of high-order modeling, aims to focus on connectivity between sets of nodes rather than pairs, whereas the second one, that of feature-rich augmentation, incorporates into a network all those elements that are driven by information which is external to the structure, like node properties or the flow of time. This paper proposes a novel toolbox, that of Attributed Stream Hypergraphs (ASHs), unifying both high-order and feature-rich elements for representing, mining, and analyzing complex networks. Applied to social network analysis, ASHs can characterize complex social phenomena along topological, dynamic and attributive elements. Experiments on real-world face-to-face and online social media interactions highlight that ASHs can easily allow for the analyses, among others, of high-order groups’ homophily, nodes’ homophily with respect to the hyperedges in which nodes participate, and time-respecting paths between hyperedges
Attributed Stream-Hypernetwork Analysis: Homophilic Behaviors in Pairwise and Group Political Discussions on Reddit
No full textComplex networks are solid models to describe human behavior. However, most analyses employing them are bounded to observations made on dyadic connectivity, whereas complex human dynamics involve higher-order relations as well. In the last few years, hypergraph models are rising as promising tools to better understand the behavior of social groups. Yet even such higher-order representations ignore the importance of the rich attributes carried by the nodes. In this work we introduce ASH, an Attributed Stream-Hypernetwork framework to model higher-order temporal networks with attributes on nodes. We leverage ASH to study pairwise and group political discussions on the well-known Reddit platform. Our analysis unveils different patterns while looking at either a pairwise or a higher-order structure for the same phenomena. In particular, we find out that Reddit users tend to surround themselves by like-minded peers with respect to their political leaning when online discussions are proxied by pairwise interactions; conversely, such a tendency significantly decreases when considering nodes embedded in higher-order contexts - that often describe heterophilic discussions
Quantifying Attraction to Extreme Opinions in Online Debates
No full textOpinion polarization and political segregation are key societal concerns, especially on social media. Although these phenomena have been traditionally attributed to homophily—preference for like-minded individuals—recent work in social psychology suggests that acrophily—preference for extreme rather than moderate opinions—might play a role as well. In this work, we introduce a methodology to estimate the degree of preference for connecting with users who hold strong opinions on social media. Our framework is composed of four phases: (i) opinion estimation, (ii) opinion thresholding, (iii) network construction, and (iv) acrophily estimation. We apply it to study the climate change debate on Reddit and find that users show higher-than-expected acrophilic patterns, especially if they are climate skeptics or have extreme opinions. Acrophilic patterns are stable over time, while polarization gradually leaves space for pluralism
Beyond Boundaries: Capturing Social Segregation on Hypernetworks
No full textIn recent years, the study of complex social systems has been fueled by the renewed interest in higher-order topologies, thus leading to the emergence of hypernetwork science. A critical and interesting phenomenon often characterizing social complex systems is segregation, i.e., the extent to which network entities are separated or clustered based on certain semantic attributes or features. This paper introduces a novel approach to studying segregation in hypernetworks. Firstly, we propose a general framework to extend classical segregation measures from dyadic to polyadic network structures. Then, we introduce a novel segregation measure called “Random Walk HyperSegregation” (RWHS), which exploits random walkers to estimate segregation at multiple scales. Through an extensive experimental study involving synthetic and real-world case studies, we illustrate the applicability and effectiveness of our measure. Moreover, we highlight the limits of classical segregation measures when extended to high-order topologies—conversely from RWHS, which effectively captured highly-segregated scenarios
FairNet: A Genetic Framework to Reduce Marginalization in Social Networks
No full textDiscrimination in social networks often assumes the form of marginalization against nodes with specific features, e.g., segregation of/against minorities. In this work, we propose a metric that proxies social discrimination based on salient node features in a social network. Under the assumption that in a fair social system, all individuals should be enclosed in similar social circles representing the network in its entirety, our metric assigns a marginalization score to each node in the network, identifying if they are marginalized by similar nodes (e.g., a man marginalized by other men), by different nodes (e.g., a man marginalized by women), or not marginalized at all (i.e., the node has a fair neighborhood). Moreover, we introduce FairNet, a two-fold framework that aims to reduce network marginalization in partially- and fully-attributed networks by employing genetic algorithms. We evaluate our framework on networks emerging from online social interactions and find that the two components of FairNet are able to consistently reduce marginalization
Bots of a feather: mixing biases in LLMs’ opinion dynamics
No full textThe rapid integration of Large Language Models (LLMs) into everyday applications raises critical questions about their group in- teractions, consensus formation, and potential to mimic human-like be- havior. Although initial research has explored the evolution of opinions within LLM populations, these efforts often rely on simplistic network assumptions, such as uniform connections among agents, thereby over- looking the influence of more realistic network topologies. This paper introduces a framework for examining opinion dynamics among LLM agents within various network structures. We perform several multi- model simulations on network topologies with known locally assorta- tive/disassortative mixing patterns. We find that convergence is quicker in mostly-disassortative networks compared to networks with no mixing biases. However, the joint effect of assortative and disassortative patterns leads to slower/no convergence
Andrea Bacová
No full textAndrea Bacová focuses on research and teaching in the field of residential architecture. Her work includes systematic research on residential buildings and their urban context. She actively participates in promoting Slovak architecture and is the author of several publications and exhibitions
Ipotesi progettuali per l’area tra Cardillo e ZEN a Palermo
No full textL'articolo descrive il lavoro di ricerca condotto nell'area tra Cardillo e ZEN a Palermo nell'ambito del progetto MIUR PRIN 2007 "Riqualificazione e aggiornamento del patrimonio di edilizia pubblica. Linee guida per gli interventi nei quartieri innovativi IACP nell’Italia centromeridionale", coordinatore nazionale prof. Benedetto Todaro - "Progetto di ricerca: Palermo: quartieri, periferie e città contemporanea", responsabile dell'unità di ricerca prof. Andrea Sciascia.
La cosa che per prima salta all’occhio giungendo presso lo ZEN di Palermo è che il quartiere risulta essere come "rinchiuso", rinchiuso non solo entro i suoi stessi confini fisici ma, principalmente, entro una sorta di isolamento sociale. Sembra non solo che la sua presenza nella piana dei Colli sia quasi quella di un corpo estraneo continuamente rigettato e rinnegato, ma anche che lo stesso contesto voglia quasi segnare un confine tra ciò che è ZEN e ciò che non lo è:
la sensazione è sia fisica che sensoriale
Viewer-, Author-, and Ownership in the Work of Andrea Zittel
No full textAndrea Zittel invites others to collapse the distinctions between artist, viewer, and collaborator by interacting with her usable works. This thesis explores the process of interacting with Zittel\u27s works, and how it affects viewer-, author- and ownership
"I'm in the Bluesky Tonight": Insights from a year worth of social data.
No full textPollution of online social spaces caused by rampaging d/misinformation is a growing societal concern. However, recent decisions to reduce access to social media APIs are causing a shortage of publicly available, recent, social media data, thus hindering the advancement of computational social science as a whole. We present a large, high-coverage dataset of social interactions and user-generated content from Bluesky Social to address this pressing issue. The dataset contains the complete post history of over 4M users (81% of all registered accounts), totalling 235M posts. We also make available social data covering follow, comment, repost, and quote interactions. Since Bluesky allows users to create and like feed generators (i.e., content recommendation algorithms), we also release the full output of several popular algorithms available on the platform, along with their timestamped "like" interactions. This dataset allows novel analysis of online behavior and human-machine engagement patterns. Notably, it provides ground-truth data for studying the effects of content exposure and self-selection and performing content virality and diffusion analysis
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