All Stories

  1. Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning
  2. RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery
  3. A Hierarchical and Disentangling Interest Learning Framework for Unbiased and True News Recommendation
  4. ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement
  5. (Vision Paper) A Vision for Spatio-Causal Situation Awareness, Forecasting, and Planning
  6. Causality Guided Disentanglement for Cross-Platform Hate Speech Detection
  7. Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification
  8. Quantifying the Echo Chamber Effect: An Embedding Distance-based Approach
  9. STREAMS: Towards Spatio-Temporal Causal Discovery with Reinforcement Learning for Streamflow Rate Prediction
  10. A Two-tier Shared Embedding Method for Review-based Recommender Systems
  11. HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer
  12. GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
  13. Causal Disentanglement for Implicit Recommendations with Network Information
  14. Data Augmentation for Deep Graph Learning
  15. Toward Graph Minimally-Supervised Learning
  16. The KDD 2022 Workshop on Causal Discovery (CD2022)
  17. Bias Mitigation for Toxicity Detection via Sequential Decisions
  18. CausalSE: Understanding Varied Spatial Effects with Missing Data Towards Adding New Bike-sharing Stations
  19. Domain Adaptive Fake News Detection via Reinforcement Learning
  20. “This is Fake! Shared it by Mistake”:Assessing the Intent of Fake News Spreaders
  21. Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies
  22. Causal Mediation Analysis with Hidden Confounders
  23. Graph Minimally-supervised Learning
  24. Graph Few-shot Class-incremental Learning
  25. Towards Anomaly-resistant Graph Neural Networks via Reinforcement Learning
  26. CauseBox
  27. Profiling Fake News Spreaders on Social Media through Psychological and Motivational Factors
  28. The KDD 2021 Workshop on Causal Discovery (CD2021)
  29. Causal Understanding of Fake News Dissemination on Social Media
  30. Adversarial Attacks and Defenses
  31. Few-shot Network Anomaly Detection via Cross-network Meta-learning
  32. Improving Cyberbullying Detection with User Interaction
  33. Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks
  34. Long-Term Effect Estimation with Surrogate Representation
  35. Graph Prototypical Networks for Few-shot Learning on Attributed Networks
  36. Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model
  37. The 5th International Workshop on Mining Actionable Insights from Social Networks (MAISoN 2020)
  38. A Survey of Learning Causality with Data
  39. Debiasing Grid-based Product Search in E-commerce
  40. Next-item Recommendation with Sequential Hypergraphs
  41. Joint Local and Global Sequence Modeling in Temporal Correlation Networks for Trending Topic Detection
  42. Causal Interpretability for Machine Learning - Problems, Methods and Evaluation
  43. A Survey on Privacy in Social Media
  44. Social Science–guided Feature Engineering
  45. #suicidal - A Multipronged Approach to Identify and Explore Suicidal Ideation in Twitter
  46. Beyond word2vec
  47. dEFEND
  48. BigScholar 2019: The 6th Workshop on Big Scholarly Data
  49. dEFEND
  50. Adaptive Unsupervised Feature Selection on Attributed Networks
  51. Learning From Networks
  52. Fake News Research
  53. Debunking Rumors in Social Networks
  54. Signed Link Prediction with Sparse Data: The Role of Personality Information
  55. Robust Cyberbullying Detection with Causal Interpretation
  56. Linked Variational AutoEncoders for Inferring Substitutable and Supplementary Items
  57. Fake News
  58. XBully
  59. Protecting User Privacy
  60. Beyond News Contents
  61. Random-Forest-Inspired Neural Networks
  62. Towards Explainable Networked Prediction
  63. Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation
  64. "Bridge"
  65. Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects
  66. Exploiting Multilabel Information for Noise-Resilient Feature Selection
  67. Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection
  68. Securing Social Media User Data
  69. Identifying Framing Bias in Online News
  70. Turning Clicks into Purchases
  71. Understanding and Identifying Rhetorical Questions in Social Media
  72. CrossFire
  73. Streaming Link Prediction on Dynamic Attributed Networks
  74. Leveraging Implicit Contribution Amounts to Facilitate Microfinancing Requests
  75. Tracing Fake-News Footprints
  76. Feature Selection
  77. Understanding and Predicting Delay in Reciprocal Relations
  78. Attributed Network Embedding for Learning in a Dynamic Environment
  79. Attributed Signed Network Embedding
  80. Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods
  81. Unsupervised Feature Selection in Signed Social Networks
  82. What Your Images Reveal
  83. A Survey of Signed Network Mining in Social Media
  84. Leveraging the Implicit Structure within Social Media for Emergent Rumor Detection
  85. Paired Restricted Boltzmann Machine for Linked Data
  86. Linked Document Embedding for Classification
  87. Replacing Mechanical Turkers? Challenges in the Evaluation of Models with Semantic Properties
  88. Recommendations in Signed Social Networks
  89. Relational Learning with Social Status Analysis
  90. Understanding and Identifying Advocates for Political Campaigns on Social Media
  91. Toward Dual Roles of Users in Recommender Systems
  92. 10 Bits of Surprise
  93. Unsupervised Streaming Feature Selection in Social Media
  94. The Fragility of Twitter Social Networks Against Suspended Users
  95. Finding the Right Social Media Site for Questions
  96. Exploring a Scalable Solution to Identifying Events in Noisy Twitter Streams
  97. Evaluation without ground truth in social media research
  98. Text, Topics, and Turkers
  99. Surpassing the Limit
  100. Predictability of Distrust with Interaction Data
  101. When is it biased?
  102. Understanding Twitter data with TweetXplorer
  103. A tool for collecting provenance data in social media
  104. Exploiting homophily effect for trust prediction
  105. Exploiting social relations for sentiment analysis in microblogging
  106. Modeling temporal effects of human mobile behavior on location-based social networks
  107. A tool for assisting provenance search in social media
  108. Seeking provenance of information using social media
  109. Mining Social Media: A Brief Introduction