Complex Networks and Their Applications XI: Proceedings of The Eleventh International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2022 - Volume 1

Part I: Information Spreading in Social Media.- Cognitive Cascades within Media Ecosystems: Simulating Fragmentation, Selective Exposure and Media Tactics to Investigate Polarization.- Properties of Reddit News Topical Interactions.- Will You Take the Knee? Italian Twitter Echo Chambers' Genesis during EURO 2020.- A simple model of knowledge scaffolding.- Using knowledge graphs to detect partisanship in online political discourse.- The wisdom_of_crowds: an efficient, philosophically-validated, social epistemological network profiling toolkit.- Opening up echo chambers via optimal content recommendation.- Change my Mind: Data Driven Estimate of Open-Mindedness from Political Discussions.- The effects of message sorting in the diffusion of information in online social media.- Gradual Network Sparsification and Georeferencing for Location-Aware Event Detection in Microblogging Services.- Manipulation during the French presidential campaign: Coordinated inauthentic behaviors and astroturfing analysis on text and images.- Part II: Modeling Human Behavior.- Lexical networks constructed to correspond students' short written responses: A quantum semantic approach.- Attributed Stream-Hypernetwork analysis: Homophilic Behaviors in Pairwise and Group Political Discussions on Reddit.- Individual Fairness for Social Media Influencers.- Multidimensional online American politics: Mining emergent social cleavages in social graphs.- Classical and quantum random walks to identify leaders in criminal networks.- Random walk for generalization in goal-directed human navigation on Wikipedia.- Sometimes Less is More: When Aggregating Networks Masks Effects.- An Adaptive Network Model Simulating the Effects of Different Culture Types and Leader Qualities on Mistake Handling and Organisational Learning.- Part III: Biological Networks.- Modeling of Hardy-Weinberg Equilibrium using dynamic random networks in an ABM framework.- IntegrOmics: A computational Framework to analyze RNA-Seq and Methylation data through heterogeneous multi-layer networks.- A Network-based Approach for Inferring Thresholds in Co-expression Networks.- Building Differential Co-expression Networks with Variable Selection and Regularization.- Inferring probabilistic Boolean networks from steady-state gene data samples.- Quantifying High-Order Interactions in Complex Physiological Networks: a frequency-specific approach.- A Novel Reverse Engineering Approach for Gene Regulatory Networks.- Using the Duplication-Divergence Network Model to Predict Protein-Protein Interactions.- Part IV: Machine Learning and Networks.- SignedS2V: structural embedding method for signed networks.- HM-LDM: A Hybrid-Membership Latent Distance Model.- The Structure of Interdisciplinary Science: Uncovering and Explaining Roles in Citation Graphs.- Inferring Parsimonious Coupling Statistics in Nonlinear Dynamics with Variational Gaussian Processes.- Detection of Sparsity in Multidimensional Data Using Network Degree Distribution and Improved Supervised Learning with Correction of Data Weighting.- Network Structure vs Chemical Information in Drug-Drug Interaction Prediction.- Geometric Deep Learning graph pruning to speed-up the run-time of Maximum Clique Enumerarion algorithms.- Graph Mining and Machine Learning for Shader Codes Analysis to Accelerate GPU Tuning.- Part V: Networks in Finance and Economics.- Pattern Analysis of Money Flows in the Bitcoin Blockchain.- On the Empirical Association between Trade Network Complexity and Global Gross Domestic Product.- Measuring the Stability of Technical Cooperation Network Based on the Nested Structure Theory.- Dynamic transition graph for estimating the predictability of financial and economical processes.- A network analysis of world trade structural changes (1996-2019).- Green Sector Space: The evolution and capabilities spillover of economic green sectors in the United States.- Statistical inference of lead-lag between asynchronous time series from p-values