Latest Articles for Social Science

A look into the structure and importance of odd cycles in graph theory.

New methods improve analysis of incomplete data in research.

A look at innovative methods for studying complex data patterns.

A look at how data cohesion improves analysis and clustering.

Learn about graphs, their properties, and real-world applications.

A look into how persistence modules aid in understanding evolving data structures.

Examining how one factor influences another through data and methods.

A model to study short-range and long-range interactions in various fields.

Bayesian methods improve survey data analysis with sparse responses, enhancing reliability.

Learn about factor models and their methods for simplifying complex data.

This article examines how networks grow through the duplication-divergence model.

Research examines citizenship norms using multilevel latent class analysis across nations.

An overview of counting logic and its impact on graph analysis.

A platform for studying advanced language models in social contexts.

Introducing methods to analyze multiple outcome dimensions in causal inference studies.

Exploring RCT rejection sampling to analyze causal effects effectively.

A study on identifying factors affecting fertility rates across countries.

Exploring the interactions and behaviors in layered cellular automata systems.

A guide to analyzing complex data using Bayesian dependent mixture models.

This paper presents a new method for matrix completion using full datasets.

Tackling missing data through innovative regression techniques for accurate insights.

Explore the complexities of hypergraphs and their real-world applications.

Collider bias can mislead research findings about the connection between exposure and outcome.

A guide to network inference and the hub model's role in analyzing group dynamics.

New techniques improve causal inference despite unobserved confounders and complex relationships.

A look at graphs and their connections to association schemes.

A look at challenges in assessing treatment impacts in interconnected systems.

A new method enhances accuracy in linking healthcare and social science data.

TSLiNGAM improves causal discovery in complex datasets with skewed distributions.

A look at correlation matrices and the Clustered Factor model's strengths and weaknesses.

A new method for analyzing political texts through word clustering.

This study focuses on new methods for understanding causal relationships.

Examining fair allocation methods for indivisible items among individuals.

Exploring how random movements lead to significant changes in behavior.

Explore a method for reliable estimation in complex data with interdependent random variables.

Explore the dynamics and significance of oscillatory networks in various fields.

Explore how networks evolve with new connections and their implications.

Exploring how individuals achieve synchronization in complex human networks.

Exploring how distribution regression aids in various fields through kernel methods.

A new model enhances detection of cohesive groups in complex networks.