601 citations · 2k across the 47 of their papers we have counts for
18 papers · 1 filter
Fact-Enhanced Synthetic News Generation
Kai Shu, Yichuan Li, Kaize Ding +1
The advanced text generation methods have witnessed great success in text summarization, language translation, and synthetic news generation. However, these techniques can be abuse…
MM-COVID: A Multilingual and Multimodal Data Repository for Combating COVID-19 Disinformation
Yichuan Li, Bohan Jiang, Kai Shu +1
The COVID-19 epidemic is considered as the global health crisis of the whole society and the greatest challenge mankind faced since World War Two. Unfortunately, the fake news abou…
Improving Cyberbully Detection with User Interaction
Suyu Ge, Lu Cheng, Huan Liu
Cyberbullying, identified as intended and repeated online bullying behavior, has become increasingly prevalent in the past few decades. Despite the significant progress made thus f…
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification
Kaize Ding, Jianling Wang, Jundong Li +2
Text classification is a critical research topic with broad applications in natural language processing. Recently, graph neural networks (GNNs) have received increasing attention i…
Topic-Preserving Synthetic News Generation: An Adversarial Deep Reinforcement Learning Approach
Ahmadreza Mosallanezhad, Kai Shu, Huan Liu
Nowadays, there exist powerful language models such as OpenAI's GPT-2 that can generate readable text and can be fine-tuned to generate text for a specific domain. Considering GPT-…
Disinformation in the Online Information Ecosystem: Detection, Mitigation and Challenges
Amrita Bhattacharjee, Kai Shu, Min Gao +1
With the rapid increase in access to internet and the subsequent growth in the population of online social media users, the quality of information posted, disseminated and consumed…
Toward Privacy and Utility Preserving Image Representation
Ahmadreza Mosallanezhad, Yasin N. Silva, Michelle V. Mancenido +1
Face images are rich data items that are useful and can easily be collected in many applications, such as in 1-to-1 face verification tasks in the domain of security and surveillan…
Causal Understanding of Fake News Dissemination on Social Media
Lu Cheng, Ruocheng Guo, Kai Shu +1
Recent years have witnessed remarkable progress towards computational fake news detection. To mitigate its negative impact, we argue that it is critical to understand what user att…
Causal Adversarial Network for Learning Conditional and Interventional Distributions
Raha Moraffah, Bahman Moraffah, Mansooreh Karami +2
We propose a generative Causal Adversarial Network (CAN) for learning and sampling from conditional and interventional distributions. In contrast to the existing CausalGAN which re…
Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model
Lu Cheng, Kai Shu, Siqi Wu +3
Social media is a vital means for information-sharing due to its easy access, low cost, and fast dissemination characteristics. However, increases in social media usage have corres…
Long-Term Effect Estimation with Surrogate Representation
Lu Cheng, Ruocheng Guo, Huan Liu
There are many scenarios where short- and long-term causal effects of an intervention are different. For example, low-quality ads may increase short-term ad clicks but decrease the…
Combating Disinformation in a Social Media Age
Kai Shu, Amrita Bhattacharjee, Faisal Alatawi +4
The creation, dissemination, and consumption of disinformation and fabricated content on social media is a growing concern, especially with the ease of access to such sources, and…
Graph Prototypical Networks for Few-shot Learning on Attributed Networks
Kaize Ding, Jianling Wang, Jundong Li +3
Attributed networks nowadays are ubiquitous in a myriad of high-impact applications, such as social network analysis, financial fraud detection, and drug discovery. As a central an…
Challenges in Combating COVID-19 Infodemic -- Data, Tools, and Ethics
Kaize Ding, Kai Shu, Yichuan Li +2
While the COVID-19 pandemic continues its global devastation, numerous accompanying challenges emerge. One important challenge we face is to efficiently and effectively use recentl…
Leveraging Multi-Source Weak Social Supervision for Early Detection of Fake News
Kai Shu, Guoqing Zheng, Yichuan Li +4
Social media has greatly enabled people to participate in online activities at an unprecedented rate. However, this unrestricted access also exacerbates the spread of misinformatio…
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation
Raha Moraffah, Mansooreh Karami, Ruocheng Guo +2
Machine learning models have had discernible achievements in a myriad of applications. However, most of these models are black-boxes, and it is obscure how the decisions are made b…
Social Science Guided Feature Engineering: A Novel Approach to Signed Link Analysis
Ghazaleh Beigi, Jiliang Tang, Huan Liu
Many real-world relations can be represented by signed networks with positive links (e.g., friendships and trust) and negative links (e.g., foes and distrust). Link prediction help…
Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements
Kai Shu, Suhang Wang, Dongwon Lee +1
In recent years, disinformation including fake news, has became a global phenomenon due to its explosive growth, particularly on social media. The wide spread of disinformation and…