Publications

Arxiv and Preprints

• A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation [pdf]
  Faisal Alatawi, Lu Cheng, Anique Tahir, Mansooreh Karami, Bohan Jiang, Tyler Black, and Huan Liu
  ArXiv. 2021.
• Toward Understanding Bias Correlations for Mitigation in NLP [pdf]
  Lu Cheng*, Suyu Ge*, and Huan Liu
  ArXiv. 2022.

Accepted Papers

• Causal Disentanglement for Implicit Recommendations with Network Information
  Paras Sheth, Ruocheng Guo, Lu Cheng, Kasim Selcuk Candan, and Huan Liu
  In TKDD’22
• Distributional Shift Adaptation using Domain-Specific Features [pdf]
  Anique Tahir, Lu Cheng, Ruocheng Guo, and Huan Liu
  In IEEE BigData’22
• Nothing Stands Alone: Leveraging News Relations through a Hypergraph for Fake News Detection [[pdf]]
  Ujun Jeong, Kaize Ding, Lu Cheng, Ruocheng Guo, Kai Shu, and Huan Liu
  In IEEE BigData’22
• Debiasing Word Embeddings with Nonlinear Geometry [pdf][code]
  Lu Cheng, Nayoung Kim, and Huan Liu
  In the 29th International Conference on Computational Linguistics (COLING). Hybrid. October 12-17, 2022.
• Classifying COVID-19 related Meta Ads using Discourse Representation through Hypergraph
  Ujun Jeong, Zeyad Alghamdi, Kaize Ding, Lu Cheng, Baoxin Li, and Huan Liu
  In the 15th SBP-BRiMS. Pittsburg. Sept. 20-22. 2022
• Improving Vaccine Stance Detection by Combining Online and Offline Data [pdf]
  Anique Tahir, Lu Cheng, Paras Sheth, and Huan Liu
  In the 15th SBP-BRiMS. Pittsburg. Sept. 20-22. 2022
• Bridging the Gap: Commonality and Differences between Online and Offline COVID-19 Data [pdf]
  Nayoung Kim, Ahmadreza Mosallanezhad, Lu Cheng, Baoxin Li, and Huan Liu
  In the 15th SBP-BRiMS. Pittsburg. Sept. 20-22. 2022
• Causal Disentanglement with Network Information for Debiased Recommendations [pdf]
  Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Selcuk Candan, Huan Liu
  SISAP 2022
• Bias Mitigation for Toxicity Detection via Sequential Decisions [pdf]
  Lu Cheng, Ahmadreza Mosallanezhad, Yasin Silva, Deborah Hall, and Huan Liu
  In SIGIR. Madrid. July 11-15, 2022.
• Evaluation Methods and Measures for Causal Learning Algorithms [pdf]
  Lu Cheng, Ruocheng Guo, Raha Moraffah, Paras Sheth, K. Selcuk Candan, and Huan Liu
  In IEEE Transactions on Artificial Intelligence (TAI). 2022.
• Learning Privacy-Preserving Graph Convolutional Network with Partially Observed Sensitive Attributes [pdf] [code]
  Hui Hu, Lu Cheng, Jayden Parker Vap, and Mike Borowczak
  In Proceedings of the ACM 2022 International World Wide Web Conferences (TheWebConf). Lyon, France. April 25-29. 2022.
• Causal Mediation Analysis with Hidden Confounders [pdf]
  Lu Cheng, Ruocheng Guo, and Huan Liu
  In Proceedings of the 2022 ACM International Conference on Web Search and Data Mining (WSDM). Online Virtual Event. Feb. 21-25. 2022.
• Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies [pdf]
  Lu Cheng, Ruocheng Guo, and Huan Liu
  In Proceedings of the 2022 ACM International Conference on Web Search and Data Mining (WSDM). Online Virtual Event. Feb. 21-25. 2022.
• Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication [pdf] [data]
  Lu Cheng, Ruocheng Guo, Kasim Selcuk Candan, and Huan Liu
  In Proceedings of the 16th International AAAI Conference on Web and Social Media (ICWSM). Atlanta, Georgia. June 6-9. 2022.
• Learning Shared Mobility-aware Knowledge for Multiple Urban Travel Demands [pdf]
  Qianru Wang, Bin Guo; Yi Ouyang, Lu Cheng, Liang Wang, Zhiwen Yu, and Huan Liu
  IEEE Internet of Things Journal. 2021.
• Mechanisms and Attributes of Echo Chambers in Social Media [pdf]
  Bohan Jiang, Mansooreh Karami, Lu Cheng, Tyler Black, and Huan Liu
  SBP-BRiMS Working Paper. 2021.
• Socially Responsible AI Algorithms: Issues, Purposes, and Challenges [pdf]
  Lu Cheng, Kush R. Varshney, and Huan Liu
  Journal of Artificial Intelligence Research. 2021.
• Causal Understanding of Fake News Dissemination on Social Media [pdf] [code]
  Lu Cheng, Ruocheng Guo, Kai Shu, and Huan Liu
  In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’21). Online Virtual Event. August 14-18, 2021.
• Mitigating Bias in Session-based Cyberbullying Detection: A Non-Compromising Approach [pdf] [code]
  Lu Cheng*, Ahmadreza Mosallanezhad*, Yasin Silva, Deborah Hall, and Huan Liu
  In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL), Bangkok, Thailand. August 1-6, 2021.
• Causal Learning for Socially Responsible AI [pdf]
  Lu Cheng, Ahmadreza Mosallanezhad, Paras Sheth, and Huan Liu
  In Proceedings of the 2021 International Joint Conferences on Artificial Intelligence (IJCAI2021), August 21-26, Montreal, Canada.
• Automated Meta-Analysis in Medical Research: A Causal Learning Perspective [poster]
  Lu Cheng, Dmitriy Katz-rogozhnikov, Ioana Baldini, and Kush R. Varshney
  In the 2021 ACM Conference on Health, Inference, and Learning Workshop. April 8-9, 2021.
• Improving Cyberbullying Detection with User Interaction [pdf] [code]
  Suyu Ge, Lu Cheng, and Huan Liu
  In Proceedings of the 2021 International World Wide Web Conference, Ljubljana, Slovenia. April 19-23, 2021.
• Modeling Temporal Patterns of Cyberbullying Detection with Hierarchical Attention Networks [pdf] [code]
  Lu Cheng, Ruocheng Guo, Yasin Silva, Deborah Hall, and Huan Liu
  ACM/IMS Transactions on Data Science. 2021.
• Long-Term Effect Estimation with Surrogate Representation [pdf] [code]
  Lu Cheng, Ruocheng Guo, and Huan Liu
  In Proceedings of the 2021 ACM International Conference on Web Search and Data Mining (WSDM), Online, March 08-12, 2021.
• Session-based Cyberbullying Detection: Problems and Challenges [pdf]
  Lu Cheng, Yasin Silva, Deborah Hall, and Huan Liu
  IEEE Internet Computing, Special Issue on Cyber-Social Health: Promoting Good and Countering Harm on Social Media, 2021
• Unsupervised Cyberbullying Detection via Time-Informed Gaussian Mixture Model [pdf] [code]
  Lu Cheng, Kai Shu, Siqi Wu, Yasin N. Silva, Deborah Hall, and Huan Liu
  In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM’20), Oct. 19-23, 2020, Online.
• BullyBlocker: Integrating Data, Computer, and Psychological Science to Identify Cyberbullying on Social Media [poster]
  Brittany Wheeler, Lu Cheng, Deborah Hall, and Yasin N. Silva
  In 2020 Women in Statistics and Data Science Conference (WSDS’20), Oct. 01-03, 2020, Pittsburgh Marriott City Center, Pittsburgh, PA, USA.
• A Survey of Learning Causality with Data: Problems and Methods [pdf]
  Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, and Huan Liu
  In ACM Computing Surveys (CSUR’20).
• Representation Learning for Imbalanced Cross-Domain Classification [pdf]
  Lu Cheng, Ruocheng Guo, K.S. Candan, and Huan Liu
  In Proceedings of the 2020 SIAM International Conferene on Data Mining (SDM’20), May 07-09, 2020, Cincinnati, Ohio, USA.
• Tracking Disaster Footprints with Social Stream Data [pdf]
  Lu Cheng, Jundong Li, K.S. Candan, and Huan Liu
  In Proceedings of 34th AAAI Conference on Artificial Intelligence (AAAI’20), Feb. 07-12, 2020, New York, New York, USA.
• A Practical Data Repository for Causal Learning with Big Data [pdf] [slides]
  Lu Cheng, Ruocheng Guo^*, Raha Moraffah^*, K.S. Candan, Adrienne Raglin, and Huan Liu
  In Proceedings of the 2019 BenchCouncil International Symposium on Benchmarking, Measuring and Optimizing (Bench’19), Nov. 14-16, 2019, Denver, Colorado, USA.
• PI-Bully: Personalized Cyberbullying Detection with Peer Influence [pdf]
  Lu Cheng, Jundong Li, Yasin N. Silva, Deborah Hall, and Huan Liu
  In Proceedings of the 2019 International Joint Conferences on Artificial Intelligence (IJCAI2019), Aug. 10-16, Macao, China.
• Robust Cyberbullying Detection with Causal Interpretation [pdf] [slides]
  Lu Cheng, Ruocheng Guo, and Huan Liu
  In Proceedings of the WWW’19 CyberSafety Workshop, May 13-17, San Francisco, U.S.
• Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network [pdf] [slides] [media coverage]
  Lu Cheng, Ruocheng Guo, Yasin N. Silva, Deborah Hall, and Huan Liu
  In Proceedings of the 2019 SIAM International Conferene on Data Mining (SDM19), Calgary, Cananda, May 2-4, 2019
• XBully: Cyberbullying Detection within a Multi-Modal Context. [pdf]
  Lu Cheng, Jundong Li, Yasin N. Silva, Deborah Hall, and Huan Liu
  In Proceedings of the 2019 ACM International Conference on Web Search and Data Mining (WSDM), Melbourne, Australia, Feb 11-15, 2019
• Personazlied Learning for Cyberbullying Detection [pdf]
  Lu Cheng, Yasin N. Silva, Deborah Hall, and Huan Liu
  SBP-BRiMS Doctoral Consortium, 2018.
• A Multi-objective Immune Genetic Algorithm for Project Scheduling on Multi-skill Resources
  Lu Cheng, Guangrui Liao, Zhenyuan Liu
  Applied Mechanics and Materials. 2014, Vol. 719-720, p1268-1274. 7p.

Peer-reviewed Posters (with poster papers or abstracts)

• BullyBlocker: Integrating Data, Computer, and Psychological Science to Identify Cyberbullying on Social Media
  B. Wheeler, L. Cheng, D. Hall, and Y. N. Silva
  The 2020 Women in Statistics and Data Science Conference (WSDS), 2020.
• An interdisciplinary investigation of temporal aspects of cyberbullying on Instagram
  W. Yang, L. Cheng, K. Schodt, C. Shao, D. Hall, and Y. N. Silva
  The Annual Meeting of the Society for Personality & Social Psychology (SPSP), Portland, OR, USA, 2019.
• An Interdisciplinary Investigation of Temporal Aspects of Cyberbullying
  L. Jiang, A. Trow, V. Delgadillo, C. Sanchez, L. Cheng, Y. Silva, D. Hall.
  The Western Psychological Association (WPA) Convention, Portland, OR, USA, 2018.
• BullyBlocker: Detecting Cyberbullying Victimization Risk through an Interdisciplinary Identification Model
  A. Trow, L. Jiang, L. Cheng, C. Sanchez, V. Delgadillo, D. Hall, Y. Silva.
  The Western Psychological Association (WPA) Convention, Portland, OR, USA, 2018.