Tootfinder

netscience: Scientific collaborations in network science (2006)
A coauthorship network among scientists working on network science, from 2006. This network is a one-mode projection from the bipartite graph of authors and their scientific publications.
This network has 1589 nodes and 2742 edges.
Tags: Social, Collaboration, Weighted, Projection

dblp_coauthor_snap: DBLP authors (2012)
A coauthorship network extracted from the DBLP computer science manuscript database, in 2012. This network is a one-mode projection from the bipartite graph of computer scientists and their publications.
This network has 425957 nodes and 1049866 edges.
Tags: Social, Collaboration, Unweighted, Metadata, Projection

Sabotage of climate action is systemic, not the result of individual actors.
Free download of ebook.
H/t @…
Global Assessment - Brown Climate Social Science Network
https://

Global Assessment - Brown Climate Social Science Network
Climate advocacy has not failed, climate policy has been sabotaged, explains a new open access book, Climate Obstruction: A Global Assessment.

A curated list of UI clients for accessing the ActivityPub Fediverse social network.
https://delightful.coding.social/delightful_fediverse_clients

delightful fediverse clients
Delightful curated lists of free software, open science and information sources.

netscience: Scientific collaborations in network science (2006)
A coauthorship network among scientists working on network science, from 2006. This network is a one-mode projection from the bipartite graph of authors and their scientific publications.
This network has 1589 nodes and 2742 edges.
Tags: Social, Collaboration, Weighted, Projection

This is just such a waste of money.
https://ec.social-network.europa.eu/@EUCommission/115343249383566862

European Commission (@EUCommission@ec.social-network.europa.eu)
Attached: 1 image Europe is upping its game in AI. Researchers, innovators & policymakers now have stronger support to shape the future of science. Today we launched two AI strategies to boost EU leadership in scientific innovation: 🥼 AI in Science 🔹Access to AI Factories & Gigafactories 🔹Stronger EU & global cooperation 🔹 Impact on major challenges such as climate change and health 🔬 Apply AI: 🔹Enhances EU tech sovereignty 🔹Targeted actions to boost AI in key secto…

Can You Hear Me Now? A Benchmark for Long-Range Graph Propagation
Luca Miglior, Matteo Tolloso, Alessio Gravina, Davide Bacciu
https://arxiv.org/abs/2512.17762 https://arxiv.org/pdf/2512.17762 https://arxiv.org/html/2512.17762
arXiv:2512.17762v1 Announce Type: new
Abstract: Effectively capturing long-range interactions remains a fundamental yet unresolved challenge in graph neural network (GNN) research, critical for applications across diverse fields of science. To systematically address this, we introduce ECHO (Evaluating Communication over long HOps), a novel benchmark specifically designed to rigorously assess the capabilities of GNNs in handling very long-range graph propagation. ECHO includes three synthetic graph tasks, namely single-source shortest paths, node eccentricity, and graph diameter, each constructed over diverse and structurally challenging topologies intentionally designed to introduce significant information bottlenecks. ECHO also includes two real-world datasets, ECHO-Charge and ECHO-Energy, which define chemically grounded benchmarks for predicting atomic partial charges and molecular total energies, respectively, with reference computations obtained at the density functional theory (DFT) level. Both tasks inherently depend on capturing complex long-range molecular interactions. Our extensive benchmarking of popular GNN architectures reveals clear performance gaps, emphasizing the difficulty of true long-range propagation and highlighting design choices capable of overcoming inherent limitations. ECHO thereby sets a new standard for evaluating long-range information propagation, also providing a compelling example for its need in AI for science.
toXiv_bot_toot

netscience: Scientific collaborations in network science (2006)
A coauthorship network among scientists working on network science, from 2006. This network is a one-mode projection from the bipartite graph of authors and their scientific publications.
This network has 1589 nodes and 2742 edges.
Tags: Social, Collaboration, Weighted, Projection

netscience: Scientific collaborations in network science (2006)
A coauthorship network among scientists working on network science, from 2006. This network is a one-mode projection from the bipartite graph of authors and their scientific publications.
This network has 1589 nodes and 2742 edges.
Tags: Social, Collaboration, Weighted, Projection

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 433 nodes and 1941 edges.
Tags: Informational, Web gra…

"All in all, these machine learning models are so good that they’ve almost completely supplanted traditional methods for detecting and phase-picking earthquakes, especially for smaller magnitudes."
"In the last five years, an AI-based workflow has almost completely replaced one of the fundamental tasks in seismology for the better."
(It's not LLMs)

“Like putting on glasses for the first time”—how AI improves earthquake detection
AI is “comically good” at detecting small earthquakes—here’s why that matters.

In Oxford for the Humanities and Data Science group AGM and public panel: what have the humanities and data science achieved in collaboration?
Our last event as an Alan Turing Institute group!
https://digitalscholarship.web.ox.ac.u

Network power: the humanities and data science in collaboration

Adaptive Science Operations in Deep Space Missions Using Offline Belief State Planning
Grace Ra Kim, Hailey Warner, Duncan Eddy, Evan Astle, Zachary Booth, Edward Balaban, Mykel J. Kochenderfer
https://arxiv.org/abs/2510.08812

Adaptive Science Operations in Deep Space Missions Using Offline Belief State Planning
Deep space missions face extreme communication delays and environmental uncertainty that prevent real-time ground operations. To support autonomous science operations in communication-constrained environments, we present a partially observable Markov decision process (POMDP) framework that adaptively sequences spacecraft science instruments. We integrate a Bayesian network into the POMDP observation space to manage the high-dimensional and uncertain measurements typical of astrobiology missions…

cs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted

Neural network topologies supporting individual variations in vividness of visual imagery https://www.sciencedirect.com/science/article/pii/S1053811925005233 "Visual imagery vividness linked to left fusiform gyrus functional efficiency";

Hi Bluesky! 👋 #datascience, broadly defined, like network science, computational social science, geospatial data science.

cs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted

wiki_science: Wikipedia Map of Science (2020)
A network of scientific fields, extracted from the English Wikipedia in early 2020. Nodes are wikipedia pages representing natural, formal, social and applied sciences, and two nodes are linked if the cosine similarity of the page content is above a threshold. See <http://www.s…

wiki_science: Wikipedia Map of Science (2020)
A network of scientific fields, extracted from the English Wikipedia in early 2020. Nodes are wikipedia pages representing natural, formal, social and applied sciences, and two nodes are linked if the cosine similarity of the page content is above a threshold. See <http://www.s…

I wrote a blog post about the often stated but never explained assumption that communities in graphs should always be connected.
This “connected cluster axiom” is inconsistent with statistical significance and null models that underlie the most widely employed methods.
https://skewed.de/lab/posts/connected-

netscience: Scientific collaborations in network science (2006)
A coauthorship network among scientists working on network science, from 2006. This network is a one-mode projection from the bipartite graph of authors and their scientific publications.
This network has 1589 nodes and 2742 edges.
Tags: Social, Collaboration, Weighted, Projection

Revealing Chaotic Dependence and Degree-Structure Mechanisms in Optimal Pinning Control of Complex Networks
Qingyang Liu (University of Science and Technology of China), Tianlong Fan (University of Science and Technology of China), Liming Pan (University of Science and Technology of China), Linyuan Lv (University of Science and Technology of China)
https://

Revealing Chaotic Dependence and Degree-Structure Mechanisms in Optimal Pinning Control of Complex Networks
Identifying an optimal set of driver nodes to achieve synchronization via pinning control is a fundamental challenge in complex network science, limited by computational intractability and the lack of general theory. Here, leveraging a degree-based mean-field (annealed) approximation from statistical physics, we analytically reveal how the structural degree distribution systematically governs synchronization performance, and derive an analytic characterization of the globally optimal pinning se…

Networks Multiscale Entropy Analysis
Sebasti\'an Brzovic, Crist\'obal Rojas, Andr\'es Abeliuk
https://arxiv.org/abs/2510.11524 https://arxiv.or…

Networks Multiscale Entropy Analysis
Understanding the structural complexity and predictability of complex networks is a central challenge in network science. Although recent studies have revealed a relationship between compression-based entropy and link prediction performance, existing methods focus on single-scale representations. This approach often overlooks the rich hierarchical patterns that can exist in real-world networks. In this study, we introduce a multiscale entropy framework that extends previous entropy-based approa…

Network topological reorganization mechanisms of primary visual cortex under multimodal stimulation (in mice) https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1678035/full

Frontiers | Network topological reorganization mechanisms of primary visual cortex under multimodal stimulation
IntroductionThe functional connectivity topology of the primary visual cortex (V1) shapes sensory processing and cross-modal integration, yet how different s...

Community Detection through Recursive Partitioning in Bayesian Framework
Yuhua Zhang, Kori S. Zachrison, Renee Y. Hsia, Jukka-Pekka Onnela
https://arxiv.org/abs/2509.23536 https…

Community Detection through Recursive Partitioning in Bayesian Framework
Community detection involves grouping the nodes in the network and is one of the most-studied tasks in network science. Conventional methods usually require the specification of the number of communities $K$ in the network. This number is determined heuristically or by certain model selection criteria. In practice, different model selection criteria yield different values of $K$, leading to different results. We propose a community detection method based on recursive partitioning within the Bay…

dblp_coauthor_snap: DBLP authors (2012)
A coauthorship network extracted from the DBLP computer science manuscript database, in 2012. This network is a one-mode projection from the bipartite graph of computer scientists and their publications.
This network has 425957 nodes and 1049866 edges.
Tags: Social, Collaboration, Unweighted, Metadata, Projection

"Due to the lapse in federal government funding, NASA is not updating this website. We sincerely regret this inconvenience." https://apod.nasa.gov/apod/

wiki_science: Wikipedia Map of Science (2020)
A network of scientific fields, extracted from the English Wikipedia in early 2020. Nodes are wikipedia pages representing natural, formal, social and applied sciences, and two nodes are linked if the cosine similarity of the page content is above a threshold. See <http://www.s…

Crosslisted article(s) found for cs.CE. https://arxiv.org/list/cs.CE/new
[1/1]:
- Neural Network Surrogates for Free Energy Computation of Complex Chemical Systems
Wasut Pornpatcharapong

netscience: Scientific collaborations in network science (2006)
A coauthorship network among scientists working on network science, from 2006. This network is a one-mode projection from the bipartite graph of authors and their scientific publications.
This network has 1589 nodes and 2742 edges.
Tags: Social, Collaboration, Weighted, Projection

Generalized Persistent Laplacians and their Spectral Properties
Arne Wolf, Jiyu Fan, Anthea Monod
https://arxiv.org/abs/2509.20220 https://arxiv.org/pdf/25…

Generalized Persistent Laplacians and their Spectral Properties
Laplacian operators are classical objects that are fundamental in both pure and applied mathematics and are becoming increasingly prominent in modern computational and data science fields such as applied and computational topology and application areas such as machine learning and network science. In this paper, we introduce a unifying operator-theoretic framework of generalized Laplacians as invariants that encompasses and extends all existing constructions, from discrete combinatorial setting…

Mapping surface height dynamics to subsurface flow physics in free-surface turbulent flow using a shallow recurrent decoder
Kristoffer S. Moen, J{\o}rgen R. Aarnes, Simen {\AA}. Ellingsen, J. Nathan Kutz
https://arxiv.org/abs/2510.06202

Mapping surface height dynamics to subsurface flow physics in free-surface turbulent flow using a shallow recurrent decoder
Near-surface turbulent flows beneath a free surface are reconstructed from sparse measurements of the surface height variation, by a novel neural network algorithm known as the SHallow REcurrent Decoder (SHRED). The reconstruction of turbulent flow fields from limited, partial, or indirect measurements remains a grand challenge in science and engineering. The central goal in such applications is to leverage easy-to-measure proxy variables in order to estimate quantities which have not been, and…

wiki_science: Wikipedia Map of Science (2020)
A network of scientific fields, extracted from the English Wikipedia in early 2020. Nodes are wikipedia pages representing natural, formal, social and applied sciences, and two nodes are linked if the cosine similarity of the page content is above a threshold. See <http://www.s…

Conformalized Gaussian processes for online uncertainty quantification over graphs
Jinwen Xu, Qin Lu, Georgios B. Giannakis
https://arxiv.org/abs/2510.06181 https://

Conformalized Gaussian processes for online uncertainty quantification over graphs
Uncertainty quantification (UQ) over graphs arises in a number of safety-critical applications in network science. The Gaussian process (GP), as a classical Bayesian framework for UQ, has been developed to handle graph-structured data by devising topology-aware kernel functions. However, such GP-based approaches are limited not only by the prohibitive computational complexity, but also the strict modeling assumptions that might yield poor coverage, especially with labels arriving on the fly. To…

Machine Learning-based Path Loss Prediction in Suburban Environment in the Sub-6 GHz Band
Ferdaous Tarhouni, Muneer AlZubi, Mohamed-Slim Alouini
https://arxiv.org/abs/2510.00696

Machine Learning-based Path Loss Prediction in Suburban Environment in the Sub-6 GHz Band
Accurate path loss (PL) prediction is crucial for successful network planning, antenna design, and performance optimization in wireless communication systems. Several conventional approaches for PL prediction have been adopted, but they have been demonstrated to lack flexibility and accuracy. In this work, we investigate the effectiveness of Machine Learning (ML) models in predicting PL, particularly for the sub-6 GHz band in a suburban campus of King Abdullah University of Science and Technolo…

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 346 nodes and 26832 edges.
Tags: Informational, Web gr…

Inspiring stories from women in astronomy in Africa
Priscilla Muheki, Mirjana Povi\'c, Somaya Saad, Salma Sylla Mbaye, in collaboration with Vanessa McBride, Naomi Asabre Frimpong, Meryem Guennoun, African Science Stars team
https://arxiv.org/abs/2510.05195

Inspiring stories from women in astronomy in Africa
In preparation for the International Astronomical Union (IAU) General Assembly (GA) 2024, the first GA held in Africa, the African Network of Women in Astronomy (AfNWA) embarked on a visionary project: the creation of an inspiring storytelling book that showcases the remarkable journeys of professional female astronomers in Africa. This book is not merely a collection of biographies; it is a tapestry of resilience, passion, and scientific excellence woven through the lives of women who have ven…

An Accelerated Newton-GMRES Method for Multilinear PageRank
Maryam Boubekraoui, Ridwane Tahiri
https://arxiv.org/abs/2509.23374 https://arxiv.org/pdf/2509.…

An Accelerated Newton-GMRES Method for Multilinear PageRank
Modeling complex multiway relationships in large-scale networks is becoming more and more challenging in data science. The multilinear PageRank problem, arising naturally in the study of higher-order Markov chains, is a powerful framework for capturing such interactions, with applications in web ranking, recommendation systems, and social network analysis. It extends the classical Google PageRank model to a tensor-based formulation, leading to a nonlinear system that captures multi-way dependen…

Neural network topologies supporting individual variations in vividness of visual imagery https://www.sciencedirect.com/science/article/pii/S1053811925005233

EpidemIQs: Prompt-to-Paper LLM Agents for Epidemic Modeling and Analysis
Mohammad Hossein Samaei, Faryad Darabi Sahneh, Lee W. Cohnstaedt, Caterina Scoglio
https://arxiv.org/abs/2510.00024

EpidemIQs: Prompt-to-Paper LLM Agents for Epidemic Modeling and Analysis
Large Language Models (LLMs) offer new opportunities to automate complex interdisciplinary research domains. Epidemic modeling, characterized by its complexity and reliance on network science, dynamical systems, epidemiology, and stochastic simulations, represents a prime candidate for leveraging LLM-driven automation. We introduce \textbf{EpidemIQs}, a novel multi-agent LLM framework that integrates user inputs and autonomously conducts literature review, analytical derivation, network modelin…

netscience: Scientific collaborations in network science (2006)
A coauthorship network among scientists working on network science, from 2006. This network is a one-mode projection from the bipartite graph of authors and their scientific publications.
This network has 1589 nodes and 2742 edges.
Tags: Social, Collaboration, Weighted, Projection

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 433 nodes and 1941 edges.
Tags: Informational, Web gra…

dblp_coauthor_snap: DBLP authors (2012)
A coauthorship network extracted from the DBLP computer science manuscript database, in 2012. This network is a one-mode projection from the bipartite graph of computer scientists and their publications.
This network has 425957 nodes and 1049866 edges.
Tags: Social, Collaboration, Unweighted, Metadata, Projection

dblp_coauthor_snap: DBLP authors (2012)
A coauthorship network extracted from the DBLP computer science manuscript database, in 2012. This network is a one-mode projection from the bipartite graph of computer scientists and their publications.
This network has 425957 nodes and 1049866 edges.
Tags: Social, Collaboration, Unweighted, Metadata, Projection

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 334 nodes and 32988 edges.
Tags: Informational, Web gr…

arxiv_collab: Scientific collaborations in physics (1995-2005)
Collaboration graphs for scientists, extracted from the Los Alamos e-Print arXiv (physics), for 1995-1999 for three categories, and additionally for 1995-2003 and 1995-2005 for one category. For copyright reasons, the MEDLINE (biomedical research) and NCSTRL (computer science) collaboration graphs from this paper are not publicly available.
This network has 8361 nodes and 15751 edges.
Tags: Social, Collaboration…

wiki_science: Wikipedia Map of Science (2020)
A network of scientific fields, extracted from the English Wikipedia in early 2020. Nodes are wikipedia pages representing natural, formal, social and applied sciences, and two nodes are linked if the cosine similarity of the page content is above a threshold. See <http://www.s…

cs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted

dblp_coauthor_snap: DBLP authors (2012)
A coauthorship network extracted from the DBLP computer science manuscript database, in 2012. This network is a one-mode projection from the bipartite graph of computer scientists and their publications.
This network has 425957 nodes and 1049866 edges.
Tags: Social, Collaboration, Unweighted, Metadata, Projection

dblp_coauthor_snap: DBLP authors (2012)
A coauthorship network extracted from the DBLP computer science manuscript database, in 2012. This network is a one-mode projection from the bipartite graph of computer scientists and their publications.
This network has 425957 nodes and 1049866 edges.
Tags: Social, Collaboration, Unweighted, Metadata, Projection

arxiv_collab: Scientific collaborations in physics (1995-2005)
Collaboration graphs for scientists, extracted from the Los Alamos e-Print arXiv (physics), for 1995-1999 for three categories, and additionally for 1995-2003 and 1995-2005 for one category. For copyright reasons, the MEDLINE (biomedical research) and NCSTRL (computer science) collaboration graphs from this paper are not publicly available.
This network has 8361 nodes and 15751 edges.
Tags: Social, Collaboration…

cs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted

cs_department: Aarhus Computer Science department relationships
Multiplex network consisting of 5 edge types corresponding to online and offline relationships (Facebook, leisure, work, co-authorship, lunch) between employees of the Computer Science department at Aarhus. Data hosted by Manlio De Domenico.
This network has 61 nodes and 620 edges.
Tags: Social, Relationships, Multilayer, Unweighted

wiki_science: Wikipedia Map of Science (2020)
A network of scientific fields, extracted from the English Wikipedia in early 2020. Nodes are wikipedia pages representing natural, formal, social and applied sciences, and two nodes are linked if the cosine similarity of the page content is above a threshold. See <http://www.s…

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

wiki_science: Wikipedia Map of Science (2020)
A network of scientific fields, extracted from the English Wikipedia in early 2020. Nodes are wikipedia pages representing natural, formal, social and applied sciences, and two nodes are linked if the cosine similarity of the page content is above a threshold. See <http://www.s…

dblp_coauthor_snap: DBLP authors (2012)
A coauthorship network extracted from the DBLP computer science manuscript database, in 2012. This network is a one-mode projection from the bipartite graph of computer scientists and their publications.
This network has 425957 nodes and 1049866 edges.
Tags: Social, Collaboration, Unweighted, Metadata, Projection

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

arxiv_collab: Scientific collaborations in physics (1995-2005)
Collaboration graphs for scientists, extracted from the Los Alamos e-Print arXiv (physics), for 1995-1999 for three categories, and additionally for 1995-2003 and 1995-2005 for one category. For copyright reasons, the MEDLINE (biomedical research) and NCSTRL (computer science) collaboration graphs from this paper are not publicly available.
This network has 16726 nodes and 47594 edges.
Tags: Social, Collaboratio…

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 433 nodes and 1941 edges.
Tags: Informational, Web gra…

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 346 nodes and 26832 edges.
Tags: Informational, Web gr…

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

arxiv_collab: Scientific collaborations in physics (1995-2005)
Collaboration graphs for scientists, extracted from the Los Alamos e-Print arXiv (physics), for 1995-1999 for three categories, and additionally for 1995-2003 and 1995-2005 for one category. For copyright reasons, the MEDLINE (biomedical research) and NCSTRL (computer science) collaboration graphs from this paper are not publicly available.
This network has 31163 nodes and 120029 edges.
Tags: Social, Collaborati…

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 300 nodes and 1155 edges.
Tags: Informational, Web gra…

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted