├── assets ├── pub_ranking_info_sys.png └── pub_ranking_data_mining.png ├── LICENSE ├── contexts └── README.md ├── .gitignore └── README.md /assets/pub_ranking_info_sys.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JihoChoi/social-network-analysis-papers/HEAD/assets/pub_ranking_info_sys.png -------------------------------------------------------------------------------- /assets/pub_ranking_data_mining.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JihoChoi/social-network-analysis-papers/HEAD/assets/pub_ranking_data_mining.png -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2018 Jiho Choi 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /contexts/README.md: -------------------------------------------------------------------------------- 1 | 2 | ________________________________________ 3 | CONTEXTS 4 | ________________________________________ 5 | 6 | Network Inference 7 | Algorithm #NetInf → #NetRate → InfoPath 8 | 9 | 1. KDD 2010 10 | Inferring Networks of Diffusion and Influence 11 | 2. ICML 2011 12 | Uncovering the Temporal Dynamics of Diffusion Networks 13 | 3. WSDM 2013 14 | Structure and Dynamics of Information Pathways in Online Media 15 | 16 | Fact-Checking System 17 | Software #Hoaxy 18 | 19 | 1. WWW 2016 20 | Hoaxy: A Platform for Tracking Online Misinformation 21 | 2. ICWSM 2018 22 | The Hoaxy Misinformation and Fact-Checking Diffusion Network 23 | 24 | Cascade - Justin Cheng 25 | 1. WWW 2014 26 | Can cascades be predicted? 27 | 2. WWW 2016 28 | Do Cascades Recur? 29 | 3. ICWSM 2018 30 | Do Diffusion Protocols Govern Cascade Growth? 31 | 32 | 33 | Dataset #FakeNewsNet 34 | 35 | 1. KDD 2017 36 | Fake News Detection on Social Media: A Data Mining Perspective 37 | 2. CMOT 2018 (Computational and Mathematical Organization Theory) 38 | FakeNewsTracker: A Tool for Fake News Collection, Detection, and Visualization 39 | 3. arXiv 2018 40 | FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media 41 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | MANIFEST 27 | 28 | # PyInstaller 29 | # Usually these files are written by a python script from a template 30 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 31 | *.manifest 32 | *.spec 33 | 34 | # Installer logs 35 | pip-log.txt 36 | pip-delete-this-directory.txt 37 | 38 | # Unit test / coverage reports 39 | htmlcov/ 40 | .tox/ 41 | .coverage 42 | .coverage.* 43 | .cache 44 | nosetests.xml 45 | coverage.xml 46 | *.cover 47 | .hypothesis/ 48 | .pytest_cache/ 49 | 50 | # Translations 51 | *.mo 52 | *.pot 53 | 54 | # Django stuff: 55 | *.log 56 | local_settings.py 57 | db.sqlite3 58 | 59 | # Flask stuff: 60 | instance/ 61 | .webassets-cache 62 | 63 | # Scrapy stuff: 64 | .scrapy 65 | 66 | # Sphinx documentation 67 | docs/_build/ 68 | 69 | # PyBuilder 70 | target/ 71 | 72 | # Jupyter Notebook 73 | .ipynb_checkpoints 74 | 75 | # pyenv 76 | .python-version 77 | 78 | # celery beat schedule file 79 | celerybeat-schedule 80 | 81 | # SageMath parsed files 82 | *.sage.py 83 | 84 | # Environments 85 | .env 86 | .venv 87 | env/ 88 | venv/ 89 | ENV/ 90 | env.bak/ 91 | venv.bak/ 92 | 93 | # Spyder project settings 94 | .spyderproject 95 | .spyproject 96 | 97 | # Rope project settings 98 | .ropeproject 99 | 100 | # mkdocs documentation 101 | /site 102 | 103 | # mypy 104 | .mypy_cache/ 105 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Social Network Analysis Papers 2 | 3 | [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/jihochoi) [![License: MIT](https://img.shields.io/badge/SNU-SCONE-red.svg)](https://github.com/jihochoi) 4 | 5 | 6 | 7 | ## Table of Contents 8 | 9 | 1. Social Network Analysis (Social Media Analysis) 10 | 2. Graph / Network Theory 11 | 3. Network Feature Extraction / Feature Engineering 12 | 4. Information Propagation / Diffusion / Cascades 13 | 5. Temporal, Dynamic Network / Evolving Network 14 | 6. Network Inference / Link Prediction 15 | 7. Influential / Influence Maximization (Estimation, Limitation) 16 | 8. Community Structure / Strong & Weak Ties 17 | 9. Graph Kernel 18 | 10. Network Embedding / Graph Neural Network 19 | 11. Miscellaneous 20 | 1. Anomaly Detection / Fake News Detection 21 | 2. Motifs and Graphlets 22 | 23 | 24 | 25 | 35 | 36 | 40 | 41 | - **Digital Libraries** 42 | - [`ACM DL`]() [`Xplore`]() [`SpringerLink`]() [`arXiv`]() [`Cornell`]() 43 | - **Badges** 44 | - [![](https://img.shields.io/badge/%20-Classic-red.svg)][0] [![](https://img.shields.io/badge/%20-Dataset-blue.svg)][0] [![](https://img.shields.io/badge/%20-Code-yellow.svg)][0] [![](https://img.shields.io/badge/%20-Algorithm-purple.svg)][0] [![](https://img.shields.io/badge/%20-Software-purple.svg)][0] [![](https://img.shields.io/badge/%20-Link-green.svg)][0] [![](https://img.shields.io/badge/%20-Survey-red.svg)][0] 45 | 46 | 49 | 50 | - **Conferences** 51 | 52 | Graph Mining / Web Search 53 | 54 | | | | | | | 55 | | ------ | ----- | ---- | ---- | ----- | 56 | | KDD | WWW | WSDM | PKDD | PAKDD | 57 | | ICDM | ICDE | CIKM | CSCW | | 58 | | ASONAM | ICWSM | | | | 59 | 60 | Representation Learning on Networks 61 | 62 | | | | | | | 63 | | ------- | ---- | ---- | ---- | ---- | 64 | | NeurIPS | ICLR | ICML | AAAI | CVPR | 65 | 66 | ### 1. Social Network Analysis (Social Media Analysis) 67 | 68 | - Measuring User Influence in Twitter: The Million Follower Fallacy (ICWSM 2010) [`AAAI`](https://www.aaai.org/ocs/index.php/ICWSM/ICWSM10/index) 69 | - What is Twitter, a Social Network or a News Media? (WWW 2010) [`ACM DL`](https://dl.acm.org/citation.cfm?id=1772751) [`PDF`](https://an.kaist.ac.kr/~haewoon/papers/2010-www-twitter.pdf) [![](https://img.shields.io/badge/%20-Classic-red.svg)](https://github.com/jihochoi) [![](https://img.shields.io/badge/%20-Dataset-blue.svg)](https://github.com/jihochoi) 70 | - Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations (KDD 2005) 71 | - Doodle Around the World: Online Scheduling Behavior Reflects Cultural Differences in Time Perception and Group Decision-Making (CSCW 2013) 72 | - BotOrNot: A System to Evaluate Social Bots (WWW 2016) [![](https://img.shields.io/badge/%20-Software-purple.svg)](https://github.com/jihochoi) 73 | - Exploring Limits to Prediction in Complex Social Systems (WWW 2016) 74 | - SNA: Characteristics of OSNs after a disaster (Information Management 2017) 75 | - Ranking Users in SNs with Higher-Order Structures (AAAI 2018) 76 | - From Data Mining to Knowledge Discovery in Databases (AAAI 1996) 77 | - Me, My Echo Chamber, and I: Introspection on Social Media Polarization (WWW 2018) 78 | 79 | ### 2. Graph / Network Theory 80 | 81 | - Emergence of Scaling in Random Networks (SCIENCE 1999) 82 | - On Power-Law Relationships of the Internet Topology (SIGCOMM 1999) 83 | - Authoritative Sources in a Hyperlinked Environment (SODA 1998) 84 | - Higher-Order Web Link Analysis Using Multilinear Algebra (ICDM 2005) 85 | 86 | ### 3. Network Feature Extraction / Feature Engineering 87 | 88 | ##### Motifs and Graphlets 89 | 90 | - Network Motifs: Simple Building Blocks of Complex Networks (Science 2002) [`Science`](http://science.sciencemag.org/content/298/5594/824) 91 | - Motifs in Temporal Networks (WSDM 2017) [`ACM DL`](https://dl.acm.org/citation.cfm?id=3018731) 92 | - Biological network comparison using graphlet degree distribution (Bioinformatics 2007) [](https://academic.oup.com/bioinformatics/article/23/2/e177/202080) 93 | - Graphlet-based Characterization of Directed Networks (Scientific Reports 2016) 94 | 95 | ### 4. Information Propagation / Diffusion / Cascades 96 | 97 | ##### Information Diffusion 98 | 99 | - On the Bursty Evolution of Blogspace (WWW 2003) 100 | - Information Diffusion Through Blogspace (WWW 2004) [![](https://img.shields.io/badge/%20-Classic-red.svg)](https://github.com/jihochoi) 101 | - Information Contagion: an Empirical Study of the Spread of News on Digg and Twitter Social Networks (AAAI 2010) 102 | - The Role of Social Networks in Information Diffusion (WWW 2012) 103 | - Structure and Dynamics of Information Pathways in Online Media (WSDM 2013) [![](https://img.shields.io/badge/%20-Algorithm-purple.svg)](https://github.com/jihochoi) 104 | - Information Diffusion in Online Social Networks: A Survey (SIGMOD 2013) 105 | - Dynamic Propagation Rates: New Dimension to Viral Marketing in OSNs (ICDM 2017) 106 | - Realtime Analysis of Information Diffusion in Social Media (VLDB 2013) 107 | 108 | ##### Information Cascades 109 | 110 | - Can cascades be predicted? (WWW 2014) 111 | - Do Cascades Recur? (WWW 2016) 112 | - The Influence of Early Respondents: Information Cascade Effects in Online Event Scheduling (WWW 2017) 113 | - Joint Modeling of Text and Networks for Cascade Prediction (ICWSM 2018) 114 | - Do Diffusion Protocols Govern Cascade Growth? (ICWSM 2018) 115 | - Cascading Behavior in Large Blog Graphs (SDM 2007) 116 | 117 | ### 5. Temporal, Dynamic Network / Evolving Network 118 | - Graphs over Time: Densification Laws, Shrinking Diameters and Possible Explanations (KDD 2005) [![](https://img.shields.io/badge/Temporal-blue.svg)](http://snap.stanford.edu/data/cit-HepPh.html) 119 | - Structural Dynamics of Knowledge Networks (ICWSM 2013) [![](https://img.shields.io/badge/Temporal-blue.svg)](http://konect.uni-koblenz.de/networks/) 120 | 121 | 122 | ### 6. Network Inference / Link Prediction 123 | 124 | - Inferring Networks of Diffusion and Influence (KDD 2010) [![](https://img.shields.io/badge/%20-Algorithm-purple.svg)](https://github.com/jihochoi) #NetInf 125 | - On the Convexity of Latent Social Network Inference (NIPS 2010) 126 | - Uncovering the Temporal Dynamics of Diffusion Networks (ICML 2011) [![](https://img.shields.io/badge/%20-Algorithm-purple.svg)](https://github.com/jihochoi) #NetRate 127 | - Efficient K-Nearest Neighbor Graph Construction for Generic Similarity Measures (WWW 2011) [`ACM DL`](https://dl.acm.org/citation.cfm?id=1963487) 128 | - Weisfeiler-Lehman Neural Machine for Link Prediction (KDD 2017) [`VIDEO`](https://youtu.be/dRC4T2gABS8) 129 | - Learning Social Network Embeddings for Predicting 130 | Information Diffusion (WSDM 2014) 131 | 132 | ### 7. Influential / Influence Maximization (Estimation, Limitation) 133 | 134 | - Maximizing the Spread of Influence through a Social Network (KDD 2003) [`ACM DL`](https://dl.acm.org/citation.cfm?id=956769) [![](https://img.shields.io/badge/%20-Classic-red.svg)](https://github.com/jihochoi) 135 | - Finding Influentials Based on the Temporal Order of Information Adoption in Twitter (WWW 2010) 136 | - Limiting the Spread of Misinformation in Social Networks (WWW 2011) 137 | - EIL: Eventual Influence Limitation 138 | - Influence Maximization in Continuous Time Diffusion Networks (ICML 2012) 139 | - Scalable Influence Estimation in Continuous-Time Diffusion Networks (NIPS 2013) [![](https://img.shields.io/badge/%20-Algorithm-purple.svg)](https://github.com/jihochoi) #ConTinEst 140 | - Portfolio Optimization for Influence Spread (WWW 2017) 141 | - Temporal Influence Blocking: Minimizing the Effect of Misinformation in Social Networks (ICDM 2017) 142 | - TIP: Temporal Influence Blocking 143 | - Exact Computation of Influence Spread by Binary Decision Diagrams (WWW 2017) 144 | - Active Opinion Maximization in Social Networks (KDD 2018) 145 | - DebateNight: The Role and Influence of Socialbots on Twitter During the 1st 2016 U.S. Presidential Debate (ICWSM 2018) [![](https://img.shields.io/badge/DebateNight-Dataset-blue.svg)](https://github.com/jihochoi) 146 | 147 | ### 8. Community Structure / Strong & Weak Ties 148 | 149 | - Statistical Properties of Community Structure in Large Social and Information Networks (WWW 2008) 150 | - Structural Role Extraction & Mining in Large Graphs (KDD 2012) [`ACM DL`](https://dl.acm.org/citation.cfm?id=2339723) 151 | - Community Interaction and Conflict on the Web (WWW 2018) 152 | 153 | ### 9. Graph Kernel 154 | - Weisfeiler-Lehman Graph Kernels (JMLR 2011) 155 | 156 | ### 10. Network Embedding / Graph Neural Network 157 | 158 | - Representation Learning on Networks [(WWW 2018 Tutorial)](http://snap.stanford.edu/proj/embeddings-www/) 159 | 160 | ##### Network Embedding 161 | 162 | - DeepWalk: Online Learning of Social Representations (KDD 2014) 163 | - LINE: Large-scale Information Network Embedding (WWW 2015) 164 | - A Survey on Network Embedding (AAAI 2018) [![](https://img.shields.io/badge/%20-Survey-red.svg)](https://github.com/jihochoi) 165 | - Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks (TKDE 2016) 166 | - Dynamic Network Embedding by Modeling Triadic Closure Process (AAAI 2018) [](https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16572) 167 | - DynamicTriad 168 | 169 | ##### Graph Neural Network / Graph Convolutional Network 170 | 171 | - The Graph Neural Network Model (Trans on NNs 2009) [`Xplore`](https://ieeexplore.ieee.org/document/4700287) 172 | - GNN 173 | - Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017) 174 | - GCN 175 | - Inductive representation learning on large graphs (NIPS 2017) [`ACM DL`](https://dl.acm.org/doi/10.5555/3294771.3294869) 176 | - GraphSAGE 177 | - Graph Attention Networks (ICLR 2018) [`arXiv`](https://arxiv.org/abs/1710.10903v3) [`WEB`](https://petar-v.com/GAT/) 178 | - Heterogeneous Graph Attention Network (WWW 2019) [`ACM DL`](https://dl.acm.org/doi/10.1145/3308558.3313562) 179 | - How Powerful are Graph Neural Networks? (ICLR 2019) 180 | - Graph Isomorphism Network (GIN) 181 | - Deep learning (nature 2015) 182 | 183 | ### 11. Miscellaneous 184 | 185 | ##### Anomaly Detection / Fake News Detection 186 | 187 | > **_This section will be separated into a different repository - [TBA: Misinformation Detection Papers](https://github.com/jihochoi)_** 188 | > . 189 | 190 | - CatchSync: Catching Synchronized Behavior in Large Directed Graphs (KDD 2014) 191 | - Fact-checking Effect on Viral Hoaxes: A Model of Misinformation Spread in Social Networks (WWW 2015) 192 | - Hoaxy: A Platform for Tracking Online Misinformation (WWW 2016) Software #Hoaxy 193 | - Fake News Detection on Social Media: A Data Mining Perspective (KDD 2017) [![](https://img.shields.io/badge/FakeNewsNet-Dataset-blue.svg)](https://github.com/jihochoi) 194 | - Fake News Detection on Social Media (KDD 2017) [![](https://img.shields.io/badge/%20-Survey-red.svg)](https://github.com/jihochoi) [![](https://img.shields.io/badge/%20-Dataset-blue.svg)](https://github.com/jihochoi) 195 | - Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems (ICDM 2017) 196 | - Tracing Fake News Footprints (WSDM 2018) 197 | - Leveraging the Crowd to Detect and Reduce the spread of Fake News and Misinformation (WSDM 2018) 198 | - The Hoaxy Misinformation and Fact-Checking Diffusion Network (ICWSM 2018) Software #Hoaxy 199 | - FakeNewsTracker: A Tool for Fake News Collection, Detection, and Visualization (CMOT 2018) [![](https://img.shields.io/badge/FakeNewsNet-Dataset-blue.svg)](https://github.com/jihochoi) 200 | (Computational and Mathematical Organization Theory) 201 | - FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media (arXiv 2018) [![](https://img.shields.io/badge/FakeNewsNet-Dataset-blue.svg)](https://github.com/jihochoi) 202 | 203 | ##### Motifs and Graphlets 204 | 205 | - Network Motifs: Simple Building Blocks of Complex Networks (Science 2002) [`Science`](http://science.sciencemag.org/content/298/5594/824) 206 | - Motifs in Temporal Networks (WSDM 2017) [`ACM DL`](https://dl.acm.org/citation.cfm?id=3018731) 207 | 208 | ### Contribution 209 | 210 | - `Pull requests` 211 | 212 | ### References 213 | 214 | - [Stanford Network Analysis Project (SANP)](http://snap.stanford.edu/) @ Stanford 215 | - [Advanced Social Network Analysis](http://incpaper.snu.ac.kr/index.php/Sna2018spring) @ Seoul National University 216 | - [CS224W Analysis of Networks](http://web.stanford.edu/class/cs224w/) @ Stanford 217 | - [CS322 Social and Information Network Analysis](http://snap.stanford.edu/na09/) @ Stanford 218 | - [Data Mining & Analysis - Google Scholar](https://scholar.google.es/citations?view_op=top_venues&hl=en&vq=eng_datamininganalysis) 219 | - [Databases & Information Systems - Google Scholar](https://scholar.google.es/citations?view_op=top_venues&hl=en&vq=eng_databasesinformationsystems) 220 | 221 | [0]: https://github.com/jihochoi 222 | --------------------------------------------------------------------------------