601 citations · 2k across the 47 of their papers we have counts for
48 papers
Social Media for Mental Health: Data, Methods, and Findings
Nur Shazwani Kamarudin, Ghazaleh Beigi, Lydia Manikonda +1
There is an increasing number of virtual communities and forums available on the web. With social media, people can freely communicate and share their thoughts, ask personal questi…
Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo
Qiang Sheng, Juan Cao, H. Russell Bernard +3
False news that spreads on social media has proliferated over the past years and has led to multi-aspect threats in the real world. While there are studies of false news on specifi…
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies
Lu Cheng, Ruocheng Guo, Huan Liu
Online reviews enable consumers to engage with companies and provide important feedback. Due to the complexity of the high-dimensional text, these reviews are often simplified as a…
Graph Few-shot Class-incremental Learning
Zhen Tan, Kaize Ding, Ruocheng Guo +1
The ability to incrementally learn new classes is vital to all real-world artificial intelligence systems. A large portion of high-impact applications like social media, recommenda…
A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation
Faisal Alatawi, Lu Cheng, Anique Tahir +4
Echo chambers on social media are a significant problem that can elicit a number of negative consequences, most recently affecting the response to COVID-19. Echo chambers promote c…
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning
Kaize Ding, Jianling Wang, James Caverlee +1
Inspired by the extensive success of deep learning, graph neural networks (GNNs) have been proposed to learn expressive node representations and demonstrated promising performance…
ICDM 2020 Knowledge Graph Contest: Consumer Event-Cause Extraction
Congqing He, Jie Zhang, Xiangyu Zhu +2
Consumer Event-Cause Extraction, the task aimed at extracting the potential causes behind certain events in the text, has gained much attention in recent years due to its wide appl…
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication
Lu Cheng, Ruocheng Guo, Kasim Selcuk Candan +1
Online review systems are the primary means through which many businesses seek to build the brand and spread their messages. Prior research studying the effects of online reviews h…
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation
Kaize Ding, Dingcheng Li, Alexander Hanbo Li +4
Paraphrase generation is a longstanding NLP task that has diverse applications for downstream NLP tasks. However, the effectiveness of existing efforts predominantly relies on larg…
Profiling Fake News Spreaders on Social Media through Psychological and Motivational Factors
Mansooreh Karami, Tahora H. Nazer, Huan Liu
The rise of fake news in the past decade has brought with it a host of consequences, from swaying opinions on elections to generating uncertainty during a pandemic. A majority of m…
Improving Fake News Detection by Using an Entity-enhanced Framework to Fuse Diverse Multimodal Clues
Peng Qi, Juan Cao, Xirong Li +7
Recently, fake news with text and images have achieved more effective diffusion than text-only fake news, raising a severe issue of multimodal fake news detection. Current studies…
NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications
Guangyi Xiao, Weiwei Xiang, Huan Liu +4
We propose a new general Graph Adversarial Domain Adaptation (GADA) based on semantic knowledge reasoning of class structure for solving the problem of unsupervised domain adaptati…
Mechanisms and Attributes of Echo Chambers in Social Media
Bohan Jiang, Mansooreh Karami, Lu Cheng +2
Echo chambers may exclude social media users from being exposed to other opinions, therefore, can cause rampant negative effects. Among abundant evidence are the 2016 and 2020 US p…
FBAdtTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements
Ujun Jeong, Kaize Ding, Huan Liu
The growing use of social media has led to drastic changes in our decision-making. Especially, Facebook offers marketing API which promotes business to target potential groups who…
Graph Learning: A Survey
Feng Xia, Ke Sun, Shuo Yu +4
Graphs are widely used as a popular representation of the network structure of connected data. Graph data can be found in a broad spectrum of application domains such as social sys…
Causal Learning for Socially Responsible AI
Lu Cheng, Ahmadreza Mosallanezhad, Paras Sheth +1
There have been increasing concerns about Artificial Intelligence (AI) due to its unfathomable potential power. To make AI address ethical challenges and shun undesirable outcomes,…
Few-shot Network Anomaly Detection via Cross-network Meta-learning
Kaize Ding, Qinghai Zhou, Hanghang Tong +1
Network anomaly detection aims to find network elements (e.g., nodes, edges, subgraphs) with significantly different behaviors from the vast majority. It has a profound impact in a…
Causal Mediation Analysis with Hidden Confounders
Lu Cheng, Ruocheng Guo, Huan Liu
An important problem in causal inference is to break down the total effect of a treatment on an outcome into different causal pathways and to quantify the causal effect in each pat…
Socially Responsible AI Algorithms: Issues, Purposes, and Challenges
Lu Cheng, Kush R. Varshney, Huan Liu
In the current era, people and society have grown increasingly reliant on artificial intelligence (AI) technologies. AI has the potential to drive us towards a future in which all…
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-…