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cs.SI updates on arXiv.org

Hiding in Plain Sight: Finding MAHA on Reddit Prism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection MV-Gate: Insider Threat Detection via Multi-View Behavioral Statistics and Semantic Modeling Algorithmic Cultivation: How Social Media Feeds Shape User Language Universal Dynamics of Punctuated Progress AI-Mediated Communication Can Steer Collective Opinion CitePrism: Human-in-the-Loop AI for Citation Auditing and Editorial Integrity Explainable Detection of Depression Status Shifts from User Digital Traces Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles Humanwashing -- It Should Leave You Feeling Dirty When Do LLMs Generate Realistic Social Networks? A Multi-Dimensional Study of Culture, Language, Scale, and Method Moltbook Moderation: Uncovering Hidden Intent Through Multi-Turn Dialogue Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks Predicting Channel Closures in the Lightning Network with Machine Learning Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence When Can Digital Personas Reliably Approximate Human Survey Findings? RAwR: Role-Aware Rewiring via Approximate Equitable Partition GravityGraphSAGE: Link Prediction in Directed Attributed Graphs Structure-Centric Graph Foundation Model via Geometric Bases Attention-based graph neural networks: a survey When AI Meets Science: Research Diversity, Interdisciplinarity, Visibility, and Retractions across Disciplines in a Global Surge Scalable inference of spatial regions and temporal signatures from time series Can LLMs Emulate Human Belief Dynamics? Predicting Post Virality with Temporal Cross-Attention over Trend Signals H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction Dynamic Graph with Similarity-Aware Attention Graph Neural Network for Recommender Systems Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks
SDG Target Interactions: The Philippine Analysis of Indiv...
Vena Pearl Bongolan, Arian Allenson M. Valdez, Roselle Leah K. R · 2021-09-12 · via cs.SI updates on arXiv.org

The United Nations developed the 17 Sustainable Development Goals (SDGs), with 169 targets, to serve as a plan for solving the world's problems and achieving a more sustainable future. This is modeled as a graph with the targets as nodes, and with the interaction between targets as the edges of the graph. An exhaustive binary comparison is done to analyze the intra- and inter-goal target interactions, entailing over 14000 comparisons. The task is to assign a 'color' to an edge: positive (indivisible), zero (consistent) or negative (cancelling). This is done via a panel of experts who will evaluate the target interactions, through a web application that was developed for coloring the edges. This is an on-going study, and so far, of the 1256 edges colored, only 36 are cancelling (negative), or 2.86%; more than 97% are positive interactions. So far, the "most negative" interactions involve: "Climate Change"; "Life Below Water"; "Peace, Justice and Strong Institutions"; and "Decent Work and Economic Growth". Most useful for planning might be the 'graph of beautiful targets' feature, which shows target with non-negative interactions, and how they connect to each other. These are the targets that may be worked on simultaneously, and currently has more than 130 nodes. This study can help researchers analyze which targets enable or constrain each other, what mitigation can be done to avoid conflicts, and can be configured for sub-national or regional study. Web app at: http://sdg-interactions.herokuapp.com/