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Social network graphs, knowledge graphs, citation networks, molecular graphs for GNN, web link graphs
322 datasets
Encompassing node and edge data for a social network analysis of the 1485 Innsbruck Inquisition, supporting an upcoming academic publication and book project. The data is curated by an author affiliated with Harvard Dataverse.
Social Network Ads likely contains data related to advertising campaigns or user interactions on social media platforms. The dataset is hosted on Kaggle, a popular platform for sharing datasets. Specific details such as the number of rows, columns, and the data's origin are unknown.
THz Satellite Weather Network Dataset contains metrics related to high-speed communication and weather conditions. The dataset's size, author, and update details are unknown.
A pre-trained model, likely a Graph Neural Network (GNN), published on Kaggle. The title suggests a focus on graph-based learning, potentially for tasks like node classification or link prediction. Specific details on architecture, training data, and performance are not provided in the available metadata.
A social network graph from LastFM users in Asia, capturing user connections and music listening habits. The dataset originates from the UCI Machine Learning Repository, a known source for benchmark datasets. Specific temporal coverage and collection details are not provided in the available metadata.
A social network graph captures friendships between users of the Last.fm music platform in Asia. The dataset's exact scale is unspecified but originates from the UCI Machine Learning Repository, a known source for benchmark data. It was likely compiled from public Last.fm API data to study online community structures.
Kaggle hosts a research dataset focused on drug interaction detection. The dataset likely contains data structured for graph neural networks and transformers, as indicated by its title. The author, organization, and specific data volume are unknown.
GraphNeuro-TGA applies graph neural networks to the task of kinetic parameter estimation. The dataset likely contains graph-structured data representing chemical or biological systems for model training and validation. It originates from Kaggle and is categorized under Research.
A framework for federated multi-modal graph neural networks designed for real-time spatial-temporal applications. The dataset likely contains graph-structured data with multiple modalities. Its author, organization, and specific size are unknown.
A research dataset from Kaggle focusing on microglial cytokine modulation using graph neural networks. The dataset's author, organization, and specific scale are not provided in the metadata. Its last update date is also unknown.
Colorado Springs data likely captures social network structures relevant to disease transmission. The dataset is authored by Richard Rothenberg and published on paperswithcode. Its specific size, format, and temporal coverage are unknown.
SumGNN is a dataset published on Kaggle. The dataset likely pertains to graph neural networks, a subfield of machine learning. Metadata is minimal; actual content requires verification after download.
Kaggle Competition Graph Dataset is a synthetic social graph connecting Kaggle users, teams, and AI competitions. It is designed for graph-based analysis and machine learning tasks.
A dataset for research on temporal graph neural networks. The data is intended for the automatic identification of project milestones. The dataset is hosted on Kaggle and is categorized for research purposes.
Research on graph neural networks focuses on improving performance under temperature variations and reducing latency. The work likely involves hardware acceleration using 3-D magnetic technology. The dataset's specific size, origin, and temporal coverage are not provided in the input.
Metadata for a knowledge graph derived from a Catholic encyclopedia. The dataset contains structured information categorized with tags including Encyclopedia, Text, Graph, and Theology. Specific details on row count, column structure, and authorship are not provided in the input.
This dataset supports molecular property prediction, specifically pIC50 values, using graph neural network ensembles. It is derived from the ChEMBL database and is tagged for graph and tabular analysis. The specific row count, column count, and data volume are not provided in the input.
A source of a graph representation of the Bengaluru metro network, including geospatial data and connectivity information. It is sourced from Kaggle and tagged for public transport, graph analysis, and the Bengaluru region.
281,903 nodes and 2,312,497 directed edges representing the hyperlink structure of Stanford University's web domain. The data captures a historical snapshot of web connectivity from 2002, organized as a directed graph where nodes are pages and edges are links.
schochastics developed this R package collection of multiple network datasets, which was last updated in March 2026. It provides a variety of graph structures for researchers and practitioners performing network analysis within the R ecosystem.