Part1. Structure.- Chapter1. Latent space generative model for bipartite networks.- Chapter2. BiMLPA : Community Detection in Bipartite Networks by Multi-Label Propagation.- Chapter3. Connected graphs with a given degree sequence: E_cient sampling, correlations, community detection and robustness.- Chapter4. An Allometric Scaling for the Number of Representative Nodes in Social Networks.- Chapter5. NeXLink: Node Embedding Framework for Cross-Network Linkages across Social Networks.- Chapter6. Improved algorithm for neuronal ensemble inference by Monte Carlo method.- Chapter7. Testing for Network and Spatial Autocorrelation.- Part2. Dynamics.- Chapter8. Approximate Identification of the Optimal Epidemic Source in Complex Networks.- Chapter9. Maxwell's Demon: Controlling Entropy via Discrete Ricci Flow over Networks.- Chapter10. Two dimensional opinion dynamics of real opinion and official stance.- Chapter11. On the Fundamental Equation of User Dynamics and the Structure of Online SocialNetworks.- Chapter12. Beyond Social Fragmentation: Coexistence of Cultural Diversity and Structural Connectivity Is Possible with Social Constituent Diversity.- Part3. .- Chapter13. Complex Networks Antifragility under Sustained Edge Attack-Repair Mechanisms.- Chapter14. How to collect private signals in information cascade : an empirical study.- Chapter15. Space geometry effect over the Internet as a physical-logical interdependent network.- Part4. .- Chapter16. The Power of Communities: A Text Classification Model with Automated Labeling Process Using Network Community Detection.- Chapter17. Effective Implementation of Energy Aware Polarization Diversity for IoT Networks Using Eigenvector Centrality.- Chapter18. Using network science to quantify economic disruptions in regional input-output networks.

This volume constitutes the proceedings of NetSci-X 2020: the Sixth International School and Conference on Network Science, which was held in Tokyo, Japan, in January 2020. NetSci-X is the Network Science Society’s winter conference series that covers a wide variety of interdisciplinary topics on networks. Participants come from various fields, including (but not limited to): mathematics, physics, computer science, social sciences, management and marketing sciences, organization science, communication science, systems science, biology, ecology, neuroscience, medicine, as well as business. This volume consists of contributed papers that have been accepted to NetSc-X 2020 through a rigorous peer review process. Researchers, students, and professionals will gain first-hand information about today’s cutting-edge research frontier of network science.