Liu, Huan

Quantifying the trustworthiness of social media content

Moturu, S. T., & Liu, H. (2011) · Distributed and Parallel Databases

Misinformation and Its ImpactsExpert finding and Q&A systems

Cited by 56

In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents

Tan, Z., Yan, J., Hsu, I.-H., Han, R., Wang, Z., Le, L. T., Song, Y., Chen, Y., Palangi, H., Lee, G., et al. (2025) · arXiv

Speech and dialogue systemsAI in Service Interactions

Cited by 54

Trust in Social Media

Tang, J., & Liu, H. (2015) · Synthesis Lectures on Information Security, Privacy, and Trust

Privacy, Security, and Data ProtectionAccess Control and Trust

Cited by 53

Improving Cyberbullying Detection with User Interaction

Ge, S., Cheng, L., & Liu, H. (2021) · Proceedings of the Web Conference 2021

Hate Speech and Cyberbullying DetectionSpam and Phishing Detection

Cited by 51

Modeling temporal patterns of cyberbullying detection with hierarchical attention networks

Cheng, L., Guo, R., Silva, Y. N., Hall, D., & Liu, H. (2021) · ACM/IMS Transactions on Data Science

Hate Speech and Cyberbullying DetectionBullying, Victimization, and Aggression

Cited by 43

Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings

Pang, G., Cao, L., Chen, L., & Liu, H. (2016) · 2016 IEEE 16th International Conference on Data Mining (ICDM)

Anomaly Detection Techniques and ApplicationsMachine Learning and Data Classification

Cited by 43

ConDA: Contrastive Domain Adaptation for AI-generated Text Detection

Bhattacharjee, A., Kumarage, T., Moraffah, R., & Liu, H. (2023) · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)

Authorship Attribution and ProfilingTopic Modeling

Cited by 43

Exploring Platform Migration Patterns between Twitter and Mastodon: A User Behavior Study

Jeong, U., Sheth, P., Tahir, A., Alatawi, F., Bernard, H. R., & Liu, H. (2024) · Proceedings of the International AAAI Conference on Web and Social Media

Media and Digital CommunicationSocial Media and Politics

Cited by 34

Stylometric Detection of AI-Generated Text in Twitter Timelines

Kumarage, T., Garland, J., Bhattacharjee, A., Trapeznikov, K., Ruston, S., & Liu, H. (2023) · arXiv

Authorship Attribution and ProfilingMisinformation and Its Impacts

Cited by 25

Can One Tamper with the Sample API?: Toward Neutralizing Bias from Spam and Bot Content

Morstatter, F., Dani, H., Sampson, J., & Liu, H. (2016) · Proceedings of the 25th International Conference Companion on World Wide Web - WWW 16 Companion

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 24

Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation

Agrawal, G., Kumarage, T., Alghamdi, Z., & Liu, H. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 23

Text Transformations in Contrastive Self-Supervised Learning: A Review

Bhattacharjee, A., Karami, M., & Liu, H. (2022) · Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 20

A Balanced Ensemble Approach to Weighting Classifiers for Text Classification

Cheong Fung, G., Yu, J., Wang, H., Cheung, D., & Liu, H. (2006) · Sixth International Conference on Data Mining (ICDM'06)

Text and Document Classification TechnologiesImbalanced Data Classification Techniques

Cited by 20

Defending Against Social Engineering Attacks in the Age of LLMs

Ai, L., Kumarage, T. S., Bhattacharjee, A., Liu, Z., Hui, Z., Davinroy, M. S., Cook, J., Cassani, L., Trapeznikov, K., Kirchner, M., et al. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Adversarial Robustness in Machine LearningSpam and Phishing Detection

Cited by 17

In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents

Tan, Z., Yan, J., Hsu, I.-H., Han, R., Wang, Z., Le, L., Song, Y., Chen, Y., Palangi, H., Lee, G., et al. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Speech and dialogue systemsAI-based Problem Solving and Planning

Cited by 16

Causal Learning for Socially Responsible AI

Cheng, L., Mosallanezhad, A., Sheth, P., & Liu, H. (2021) · Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 15

How Reliable Are AI-Generated-Text Detectors? An Assessment Framework Using Evasive Soft Prompts

Kumarage, T., Sheth, P., Moraffah, R., Garland, J., & Liu, H. (2023) · arXiv

Adversarial Robustness in Machine LearningAuthorship Attribution and Profiling

Cited by 11

Bias Mitigation for Toxicity Detection via Sequential Decisions

Cheng, L., Mosallanezhad, A., Silva, Y. N., Hall, D. L., & Liu, H. (2022) · Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Hate Speech and Cyberbullying DetectionEthics and Social Impacts of AI

Cited by 8

Physics-Informed Graph Learning

Peng, C., Xia, F., Saikrishna, V., & Liu, H. (2022) · arXiv

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 8

Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens

Zhao, C., Tan, Z., Ma, P., Li, D., Jiang, B., Wang, Y., Yang, Y., & Liu, H. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 5

ConDA: Contrastive Domain Adaptation for AI-generated Text Detection

Bhattacharjee, A., Kumarage, T., Moraffah, R., & Liu, H. (2023) · arXiv

Authorship Attribution and ProfilingTopic Modeling

Cited by 3