| 2026 | ACL | DisastQA: A Comprehensive Benchmark for Evaluating Question Answering in Disaster Management. | Zhitong Chen, Kai Yin, Xiangjue Dong, Chengkai Liu, Xiangpeng Li, Bo Li, Junwei Ma, Yiming Xiao, Ali Mostafavi, James Caverlee |
| 2026 | ACL | CHOIR: Harmonizing Structured Persona Diversity for Robust Collaborative LLM Reasoning. | Xiangjue Dong, Cong Wang, Maria Teleki, Millennium Bismay, Ruihong Huang, James Caverlee |
| 2026 | ACL | DMRetriever: A Family of Models for Improved Text Retrieval in Disaster Management. | Kai Yin, Xiangjue Dong, Chengkai Liu, Allen Lin, Lingfeng Shi, Ali Mostafavi, James Caverlee |
| 2026 | CHI | PromptHelper: A Prompt Recommender System for Encouraging Creativity in AI Chatbot Interactions. | Jason Kim, Maria Teleki, James Caverlee |
| 2026 | LREC | Language Models as Semantic Augmenters for Sequential Recommenders. | Mahsa Valizadeh, Xiangjue Dong, Rui Tuo, James Caverlee |
| 2026 | WSDM | Personalization in the Era of Super(?)-intelligence. | James Caverlee |
| 2026 | WSDM | Third Workshop on Generative AI for Recommender Systems and Personalization. | Narges Tabari, Aniket Deshmukh, Wang-Cheng Kang, Julian J. McAuley, James Caverlee, Neil Shah, George Karypis |
| 2025 | AAAI | Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation. | Haoran Liu, Youzhi Luo, Tianxiao Li, James Caverlee, Martin Renqiang Min |
| 2025 | ACL | GraphCheck: Breaking Long-Term Text Barriers with Extracted Knowledge Graph-Powered Fact-Checking. | Yingjian Chen, Haoran Liu, Yinhong Liu, Jinxiang Xie, Rui Yang, Han Yuan, Yanran Fu, Peng Yuan Zhou, Qingyu Chen, James Caverlee, Irene Li |
| 2025 | EMNLP | A Survey on LLMs for Story Generation. | Maria Teleki, Vedangi Bengali, Xiangjue Dong, Sai Janjur, Haoran Liu, Tian Liu, Cong Wang, Ting Liu, Yin Zhang, Frank Shipman, James Caverlee |
| 2025 | EMNLP | DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster Management. | Kai Yin, Xiangjue Dong, Chengkai Liu, Lipai Huang, Yiming Xiao, Zhewei Liu, Ali Mostafavi, James Caverlee |
| 2025 | Interspeech | I want a horror - comedy - movie: Slips-of-the-Tongue Impact Conversational Recommender System Performance. | Maria Teleki, Lingfeng Shi, Chengkai Liu, James Caverlee |
| 2025 | ICWSM | Masculine Defaults via Gendered Discourse in Podcasts and Large Language Models. | Maria Teleki, Xiangjue Dong, Haoran Liu, James Caverlee |
| 2025 | KDD | Flow Matching for Collaborative Filtering. | Chengkai Liu, Yangtian Zhang, Jianling Wang, Rex Ying, James Caverlee |
| 2025 | KDD | Second Workshop on Generative AI for Recommender Systems and Personalization. | Narges Tabari, Aniket Deshmukh, Wang-Cheng Kang, Julian J. McAuley, James Caverlee, Neil Shah, George Karypis |
| 2025 | NAACL | ReasoningRec: Bridging Personalized Recommendations and Human-Interpretable Explanations through LLM Reasoning. | Millennium Bismay, Xiangjue Dong, James Caverlee |
| 2025 | WSDM | Combating Heterogeneous Model Biases in Recommendations via Boosting. | Jinhao Pan, James Caverlee, Ziwei Zhu |
| 2024 | CIKM | Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation. | Chengkai Liu, Jianghao Lin, Hanzhou Liu, Jianling Wang, James Caverlee |
| 2024 | COLING | DACL: Disfluency Augmented Curriculum Learning for Fluent Text Generation. | Rohan Chaudhury, Maria Teleki, Xiangjue Dong, James Caverlee |
| 2024 | COLING | Quantifying the Impact of Disfluency on Spoken Content Summarization. | Maria Teleki, Xiangjue Dong, James Caverlee |
| 2024 | CVPR | The Neglected Tails in Vision-Language Models. | Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, Shu Kong |
| 2024 | ECIR | Federated Conversational Recommender Systems. | Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee |
| 2024 | ECIR | Countering Mainstream Bias via End-to-End Adaptive Local Learning. | Jinhao Pan, Ziwei Zhu, Jianling Wang, Allen Lin, James Caverlee |
| 2024 | EMNLP | Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion. | Guanchu Wang, Yu-Neng Chuang, Ruixiang Tang, Shaochen Zhong, Jiayi Yuan, Hongye Jin, Zirui Liu, Vipin Chaudhary, Shuai Xu, James Caverlee, Xia Ben Hu |
| 2024 | EMNLP | DA³: A Distribution-Aware Adversarial Attack against Language Models. | Yibo Wang, Xiangjue Dong, James Caverlee, Philip S. Yu |
| 2024 | EMNLP | FANTAstic SEquences and Where to Find Them: Faithful and Efficient API Call Generation through State-tracked Constrained Decoding and Reranking. | Zhuoer Wang, Leonardo F. R. Ribeiro, Alexandros Papangelis, Rohan Mukherjee, Tzu-Yen Wang, Xinyan Zhao, Arijit Biswas, James Caverlee, Angeliki Metallinou |
| 2024 | Interspeech | Comparing ASR Systems in the Context of Speech Disfluencies. | Maria Teleki, Xiangjue Dong, Soohwan Kim, James Caverlee |
| 2024 | RecSys | Improving Data Efficiency for Recommenders and LLMs. | Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, James Caverlee, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng |
| 2024 | WWW | Everything Perturbed All at Once: Enabling Differentiable Graph Attacks. | Haoran Liu, Bokun Wang, Jianling Wang, Xiangjue Dong, Tianbao Yang, James Caverlee |
| 2024 | WWW | Large Language Models as Data Augmenters for Cold-Start Item Recommendation. | Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen |
| 2023 | ACL | PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts. | Xiangjue Dong, Yun He, Ziwei Zhu, James Caverlee |
| 2023 | EACL | Closed-book Question Generation via Contrastive Learning. | Xiangjue Dong, Jiaying Lu, Jianling Wang, James Caverlee |
| 2023 | EACL | Reinforced Sequence Training based Subjective Bias Correction. | Karthic Madanagopal, James Caverlee |
| 2023 | ECIR | Evolution of Filter Bubbles and Polarization in News Recommendation. | Han Zhang, Ziwei Zhu, James Caverlee |
| 2023 | EMNLP | Co²PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning. | Xiangjue Dong, Ziwei Zhu, Zhuoer Wang, Maria Teleki, James Caverlee |
| 2023 | EMNLP | Bias Neutralization in Non-Parallel Texts: A Cyclic Approach with Auxiliary Guidance. | Karthic Madanagopal, James Caverlee |
| 2023 | EMNLP | Unsupervised Candidate Answer Extraction through Differentiable Masker-Reconstructor Model. | Zhuoer Wang, Yicheng Wang, Ziwei Zhu, James Caverlee |
| 2023 | KDD | Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). | Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi |
| 2023 | RecSys | Incorporating Time in Sequential Recommendation Models. | Mostafa Rahmani, James Caverlee, Fei Wang |
| 2023 | WWW | Enhancing User Personalization in Conversational Recommenders. | Allen Lin, Ziwei Zhu, Jianling Wang, James Caverlee |
| 2022 | AAAI | Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. | Kaize Ding, Jianling Wang, James Caverlee, Huan Liu |
| 2022 | AAAI | RES: An Interpretable Replicability Estimation System for Research Publications. | Zhuoer Wang, Qizhang Feng, Mohinish Chatterjee, Xing Zhao, Yezi Liu, Yuening Li, Abhay Kumar Singh, Frank M. Shipman III, Xia Hu, James Caverlee |
| 2022 | CIKM | Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems. | Allen Lin, Jianling Wang, Ziwei Zhu, James Caverlee |
| 2022 | WWW | MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks. | Yun He, Xue Feng, Cheng Cheng, Geng Ji, Yunsong Guo, James Caverlee |
| 2022 | WWW | Improving Linguistic Bias Detection in Wikipedia using Cross-Domain Adaptive Pre-Training. | Karthic Madanagopal, James Caverlee |
| 2022 | WSDM | Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning. | Ziwei Zhu, James Caverlee |
| 2021 | KDD | Popularity Bias in Dynamic Recommendation. | Ziwei Zhu, Yun He, Xing Zhao, James Caverlee |
| 2021 | WWW | Towards Ongoing Detection of Linguistic Bias on Wikipedia. | Karthic Madanagopal, James Caverlee |
| 2021 | WWW | Rabbit Holes and Taste Distortion: Distribution-Aware Recommendation with Evolving Interests. | Xing Zhao, Ziwei Zhu, James Caverlee |
| 2021 | SIGIR | Sequential Recommendation for Cold-start Users with Meta Transitional Learning. | Jianling Wang, Kaize Ding, James Caverlee |
| 2021 | SIGIR | Fairness among New Items in Cold Start Recommender Systems. | Ziwei Zhu, Jingu Kim, Trung Nguyen, Aish Fenton, James Caverlee |
| 2021 | WSDM | Popularity-Opportunity Bias in Collaborative Filtering. | Ziwei Zhu, Yun He, Xing Zhao, Yin Zhang, Jianling Wang, James Caverlee |
| 2021 | SDM | Session-based Recommendation with Hypergraph Attention Networks. | Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee |
| 2020 | CHI | Towards an Automated Writing Assistant for Online Reviews. | Parisa Kaghazgaran, James Caverlee |
| 2020 | ECIR | Recommending Music Curators: A Neural Style-Aware Approach. | Jianling Wang, James Caverlee |
| 2020 | EMNLP | PARADE: A New Dataset for Paraphrase Identification Requiring Computer Science Domain Knowledge. | Yun He, Zhuoer Wang, Yin Zhang, Ruihong Huang, James Caverlee |
| 2020 | EMNLP | Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition. | Yun He, Ziwei Zhu, Yin Zhang, Qin Chen, James Caverlee |
| 2020 | RecSys | Content-Collaborative Disentanglement Representation Learning for Enhanced Recommendation. | Yin Zhang, Ziwei Zhu, Yun He, James Caverlee |
| 2020 | RecSys | Unbiased Implicit Recommendation and Propensity Estimation via Combinational Joint Learning. | Ziwei Zhu, Yun He, Yin Zhang, James Caverlee |
| 2020 | WWW | Adaptive Hierarchical Translation-based Sequential Recommendation. | Yin Zhang, Yun He, Jianling Wang, James Caverlee |
| 2020 | WWW | Addressing the Target Customer Distortion Problem in Recommender Systems. | Xing Zhao, Ziwei Zhu, Majid Alfifi, James Caverlee |
| 2020 | SIGIR | ADORE: Aspect Dependent Online REview Labeling for Review Generation. | Parisa Kaghazgaran, Jianling Wang, Ruihong Huang, James Caverlee |
| 2020 | SIGIR | Next-item Recommendation with Sequential Hypergraphs. | Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, James Caverlee |
| 2020 | SIGIR | Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation. | Ziwei Zhu, Shahin Sefati, Parsa Saadatpanah, James Caverlee |
| 2020 | SIGIR | Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems. | Ziwei Zhu, Jianling Wang, James Caverlee |
| 2020 | WSDM | Consistency-Aware Recommendation for User-Generated Item List Continuation. | Yun He, Yin Zhang, Weiwen Liu, James Caverlee |
| 2020 | WSDM | Key Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion. | Jianling Wang, Kaize Ding, Ziwei Zhu, Yin Zhang, James Caverlee |
| 2020 | WSDM | Time to Shop for Valentine's Day: Shopping Occasions and Sequential Recommendation in E-commerce. | Jianling Wang, Raphael Louca, Diane Hu, Caitlin Cellier, James Caverlee, Liangjie Hong |
| 2020 | WSDM | User Recommendation in Content Curation Platforms. | Jianling Wang, Ziwei Zhu, James Caverlee |
| 2020 | WSDM | Improving the Estimation of Tail Ratings in Recommender System with Multi-Latent Representations. | Xing Zhao, Ziwei Zhu, Yin Zhang, James Caverlee |
| 2019 | CIKM | A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists. | Yun He, Jianling Wang, Wei Niu, James Caverlee |
| 2019 | CIKM | Wide-Ranging Review Manipulation Attacks: Model, Empirical Study, and Countermeasures. | Parisa Kaghazgaran, Majid Alfifi, James Caverlee |
| 2019 | CIKM | Instagrammers, Fashionistas, and Me: Recurrent Fashion Recommendation with Implicit Visual Influence. | Yin Zhang, James Caverlee |
| 2019 | ICWSM | A Large-Scale Study of ISIS Social Media Strategy: Community Size, Collective Influence, and Behavioral Impact. | Majid Alfifi, Parisa Kaghazgaran, James Caverlee, Fred Morstatter |
| 2019 | ICWSM | TOmCAT: Target-Oriented Crowd Review Attacks and Countermeasures. | Parisa Kaghazgaran, Majid Alfifi, James Caverlee |
| 2019 | PAKDD | An Interpretable Neural Model with Interactive Stepwise Influence. | Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu |
| 2019 | WWW | Improving Top-K Recommendation via JointCollaborative Autoencoders. | Ziwei Zhu, Jianling Wang, James Caverlee |
| 2019 | WSDM | Recurrent Recommendation with Local Coherence. | Jianling Wang, James Caverlee |
| 2018 | AAAI | Location-Sensitive User Profiling Using Crowdsourced Labels. | Wei Niu, James Caverlee, Haokai Lu |
| 2018 | CIKM | Behavior-based Community Detection: Application to Host Assessment In Enterprise Information Networks. | Cheng Cao, Zhengzhang Chen, James Caverlee, Lu-An Tang, Chen Luo, Zhichun Li |
| 2018 | CIKM | Fairness-Aware Tensor-Based Recommendation. | Ziwei Zhu, Xia Hu, James Caverlee |
| 2018 | ICDE | DisTenC: A Distributed Algorithm for Scalable Tensor Completion on Spark. | Hancheng Ge, Kai Zhang, Majid Alfifi, Xia Hu, James Caverlee |
| 2018 | ICDM | Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation. | Yun He, Haochen Chen, Ziwei Zhu, James Caverlee |
| 2018 | RecSys | Quality-aware neural complementary item recommendation. | Yin Zhang, Haokai Lu, Wei Niu, James Caverlee |
| 2018 | RecSys | TrailMix: An Ensemble Recommender System for Playlist Curation and Continuation. | Xing Zhao, Qingquan Song, James Caverlee, Xia Hu |
| 2018 | SIGIR | Learning Geo-Social User Topical Profiles with Bayesian Hierarchical User Factorization. | Haokai Lu, Wei Niu, James Caverlee |
| 2018 | WSDM | Combating Crowdsourced Review Manipulators: A Neighborhood-Based Approach. | Parisa Kaghazgaran, James Caverlee, Anna Cinzia Squicciarini |
| 2018 | WSDM | Neural Personalized Ranking for Image Recommendation. | Wei Niu, James Caverlee, Haokai Lu |
| 2017 | ICDCS | Dynamic Contract Design for Heterogenous Workers in Crowdsourcing for Quality Control. | Chenxi Qiu, Anna Cinzia Squicciarini, Sarah Michele Rajtmajer, James Caverlee |
| 2017 | ICWSM | Behavioral Analysis of Review Fraud: Linking Malicious Crowdsourcing to Amazon and Beyond. | Parisa Kaghazgaran, James Caverlee, Majid Alfifi |
| 2017 | KDD | Multi-Aspect Streaming Tensor Completion. | Qingquan Song, Xiao Huang, Hancheng Ge, James Caverlee, Xia Hu |
| 2017 | RANLP | Online Deception Detection Refueled by Real World Data Collection. | Wenlin Yao, Zeyu Dai, Ruihong Huang, James Caverlee |
| 2017 | SIGIR | What Are You Known For?: Learning User Topical Profiles with Implicit and Explicit Footprints. | Cheng Cao, Hancheng Ge, Haokai Lu, Xia Hu, James Caverlee |
| 2017 | SIGIR | Crowdsourced App Review Manipulation. | Shanshan Li, James Caverlee, Wei Niu, Parisa Kaghazgaran |
| 2016 | AAAI | College Towns, Vacation Spots, and Tech Hubs: Using Geo-Social Media to Model and Compare Locations. | Hancheng Ge, James Caverlee |
| 2016 | CIKM | Uncovering the Spatio-Temporal Dynamics of Memes in the Presence of Incomplete Information. | Hancheng Ge, James Caverlee, Nan Zhang, Anna Cinzia Squicciarini |
| 2016 | CIKM | CrowdSelect: Increasing Accuracy of Crowdsourcing Tasks through Behavior Prediction and User Selection. | Chenxi Qiu, Anna Cinzia Squicciarini, Barbara Carminati, James Caverlee, Dev Rishi Khare |
| 2016 | ECIR | LExL: A Learning Approach for Local Expert Discovery on Twitter. | Wei Niu, Zhijiao Liu, James Caverlee |
| 2016 | RecSys | TAPER: A Contextual Tensor-Based Approach for Personalized Expert Recommendation. | Hancheng Ge, James Caverlee, Haokai Lu |
| 2016 | RecSys | Discovering What You're Known For: A Contextual Poisson Factorization Approach. | Haokai Lu, James Caverlee, Wei Niu |
| 2015 | CIKM | Organic or Organized?: Exploring URL Sharing Behavior. | Cheng Cao, James Caverlee, Kyumin Lee, Hancheng Ge, Jin-Wook Chung |
| 2015 | CIKM | BiasWatch: A Lightweight System for Discovering and Tracking Topic-Sensitive Opinion Bias in Social Media. | Haokai Lu, James Caverlee, Wei Niu |
| 2015 | ECIR | Detecting Spam URLs in Social Media via Behavioral Analysis. | Cheng Cao, James Caverlee |
| 2015 | ECIR | A Noise-Filtering Approach for Spatio-temporal Event Detection in Social Media. | Yuan Liang, James Caverlee, Cheng Cao |
| 2015 | ICWSM | Crowds, Gigs, and Super Sellers: A Measurement Study of a Supply-Driven Crowdsourcing Marketplace. | Hancheng Ge, James Caverlee, Kyumin Lee |
| 2015 | RecSys | Exploiting Geo-Spatial Preference for Personalized Expert Recommendation. | Haokai Lu, James Caverlee |
| 2015 | SIGIR | SIGIR 2015 Workshop on Temporal, Social and Spatially-aware Information Access (#TAIA2015). | Klaus Berberich, James Caverlee, Miles Efron, Claudia Hauff, Vanessa Murdock, Milad Shokouhi, Bart Thomee |
| 2015 | SIGIR | Uncovering Crowdsourced Manipulation of Online Reviews. | Amir Fayazi, Kyumin Lee, James Caverlee, Anna Cinzia Squicciarini |
| 2015 | WISE | Creating Diverse Product Review Summaries: A Graph Approach. | Natwar Modani, Elham Khabiri, Harini Srinivasan, James Caverlee |
| 2014 | CIKM | DUBMOD14 - International Workshop on Data-driven User Behavioral Modeling and Mining from Social Media. | Jalal Mahmud, Jeffrey Nichols, Michelle X. Zhou, James Caverlee, Yi Zeng, Liang Chen, John O'Donovan |
| 2014 | WWW | Finding local experts on twitter. | Zhiyuan Cheng, James Caverlee, Himanshu Barthwal, Vandana Bachani |
| 2014 | WWW | Social spam, campaigns, misinformation and crowdturfing. | Kyumin Lee, James Caverlee, Calton Pu |
| 2014 | SIGIR | Who is the barbecue king of texas?: a geo-spatial approach to finding local experts on twitter. | Zhiyuan Cheng, James Caverlee, Himanshu Barthwal, Vandana Bachani |
| 2013 | CIKM | Spatio-temporal meme prediction: learning what hashtags will be popular where. | Krishna Yeswanth Kamath, James Caverlee |
| 2013 | CIKM | DUBMOD13: international workshop on data-driven user behavioral modelling and mining from social media. | Jalal Mahmud, Jeffrey Nichols, Michelle X. Zhou, James Caverlee, John O'Donovan |
| 2013 | CIKM | Location prediction in social media based on tie strength. | Jeffrey McGee, James Caverlee, Zhiyuan Cheng |
| 2013 | ICWSM | Combating Threats to Collective Attention in Social Media: An Evaluation. | Kyumin Lee, Krishna Yeswanth Kamath, James Caverlee |
| 2013 | ICWSM | Crowdturfers, Campaigns, and Social Media: Tracking and Revealing Crowdsourced Manipulation of Social Media. | Kyumin Lee, Prithivi Tamilarasan, James Caverlee |
| 2013 | WWW | Spatio-temporal dynamics of online memes: a study of geo-tagged tweets. | Krishna Yeswanth Kamath, James Caverlee, Kyumin Lee, Zhiyuan Cheng |
| 2013 | WWW | Board coherence in Pinterest: non-visual aspects of a visual site. | Krishna Yeswanth Kamath, Ana-Maria Popescu, James Caverlee |
| 2013 | WWW | Text vs. images: on the viability of social media to assess earthquake damage. | Yuan Liang, James Caverlee, John Mander |
| 2012 | CIKM | Content-based crowd retrieval on the real-time web. | Krishna Yeswanth Kamath, James Caverlee |
| 2012 | CIKM | Spatial influence vs. community influence: modeling the global spread of social media. | Krishna Yeswanth Kamath, James Caverlee, Zhiyuan Cheng, Daniel Z. Sui |
| 2012 | CIKM | DUBMMSM'12: international workshop on data-driven user behavioral modeling and mining from social media. | Jalal Mahmud, James Caverlee, Jeffrey Nichols, John O'Donovan, Michelle X. Zhou |
| 2012 | WWW | Detecting collective attention spam. | Kyumin Lee, James Caverlee, Krishna Yeswanth Kamath, Zhiyuan Cheng |
| 2011 | CIKM | Toward traffic-driven location-based web search. | Zhiyuan Cheng, James Caverlee, Krishna Yeswanth Kamath, Kyumin Lee |
| 2011 | CIKM | Discovering trending phrases on information streams. | Krishna Yeswanth Kamath, James Caverlee |
| 2011 | CIKM | Content-driven detection of campaigns in social media. | Kyumin Lee, James Caverlee, Zhiyuan Cheng, Daniel Z. Sui |
| 2011 | CIKM | A geographic study of tie strength in social media. | Jeffrey McGee, James Caverlee, Zhiyuan Cheng |
| 2011 | ICWSM | Exploring Millions of Footprints in Location Sharing Services. | Zhiyuan Cheng, James Caverlee, Kyumin Lee, Daniel Z. Sui |
| 2011 | ICWSM | Summarizing User-Contributed Comments. | Elham Khabiri, James Caverlee, Chiao-Fang Hsu |
| 2011 | ICWSM | Seven Months with the Devils: A Long-Term Study of Content Polluters on Twitter. | Kyumin Lee, Brian David Eoff, James Caverlee |
| 2011 | SAC | Hierarchical comments-based clustering. | Chiao-Fang Hsu, James Caverlee, Elham Khabiri |
| 2011 | SIGIR | CrowdTracker: enabling community-based real-time web monitoring. | James Caverlee, Zhiyuan Cheng, Brian Eoff, Chiao-Fang Hsu, Krishna Yeswanth Kamath, Jeffrey McGee |
| 2011 | WSDM | Transient crowd discovery on the real-time social web. | Krishna Yeswanth Kamath, James Caverlee |
| 2010 | CIKM | You are where you tweet: a content-based approach to geo-locating twitter users. | Zhiyuan Cheng, James Caverlee, Kyumin Lee |
| 2010 | CIKM | Identifying hotspots on the real-time web. | Krishna Yeswanth Kamath, James Caverlee |
| 2010 | GRC | A Summary of Granular Computing System Vulnerabilities: Exploring the Dark Side of Social Networking Communities. | Steve Webb, James Caverlee, Calton Pu |
| 2010 | ICWSM | Devils, Angels, and Robots: Tempting Destructive Users in Social Media. | Kyumin Lee, Brian David Eoff, James Caverlee |
| 2010 | WWW | The social honeypot project: protecting online communities from spammers. | Kyumin Lee, James Caverlee, Steve Webb |
| 2010 | SIGIR | Uncovering social spammers: social honeypots + machine learning. | Kyumin Lee, James Caverlee, Steve Webb |
| 2009 | ICWSM | A Categorical Model for Discovering Latent Structure in Social Annotations. | Said Kashoob, James Caverlee, Ying Ding |
| 2009 | ICWSM | Analyzing and Predicting Community Preference of Socially Generated Metadata: A Case Study on Comments in the Digg Community. | Elham Khabiri, Chiao-Fang Hsu, James Caverlee |
| 2008 | CIKM | Predicting web spam with HTTP session information. | Steve Webb, James Caverlee, Calton Pu |
| 2008 | ICWSM | A Large-Scale Study of MySpace: Observations and Implications for Online Social Networks. | James Caverlee, Steve Webb |
| 2008 | WWW | Towards robust trust establishment in web-based social networks with socialtrust. | James Caverlee, Ling Liu, Steve Webb |
| 2008 | WWW | Plurality: a context-aware personalized tagging system. | Robert Graham, Brian Eoff, James Caverlee |
| 2007 | ICDE | DSphere: A Source-Centric Approach to Crawling, Indexing and Searching the World Wide Web. | Bhuvan Bamba, Ling Liu, James Caverlee, Vaibhav Padliya, Mudhakar Srivatsa, Tushar Bansal, Mahesh Palekar, Joseph Patrao, Suiyang Li, Aameek Singh |
| 2007 | PODC | Countering web spam with credibility-based link analysis. | James Caverlee, Ling Liu |
| 2006 | BPM | Process Mining by Measuring Process Block Similarity. | Joonsoo Bae, James Caverlee, Ling Liu, Hua Yan |
| 2006 | ICWS | Process Mining, Discovery, and Integration using Distance Measures. | Joonsoo Bae, Ling Liu, James Caverlee, William B. Rouse |
| 2006 | SIGIR | Distributed query sampling: a quality-conscious approach. | James Caverlee, Ling Liu, Joonsoo Bae |
| 2005 | ICWS | Domain-Specific Web Service Discovery with Service Class Descriptions. | Daniel Rocco, James Caverlee, Ling Liu, Terence Critchlow |
| 2005 | WWW | Exploiting the deep web with DynaBot: matching, probing, and ranking. | Daniel Rocco, James Caverlee, Ling Liu, Terence Critchlow |
| 2005 | WEBIST | XPACK: A High-Performance WEB Document Encoding. | Daniel Rocco, James Caverlee, Ling Liu |
| 2004 | ICDE | Probe, Cluster, and Discover: Focused Extraction of QA-Pagelets from the Deep Web. | James Caverlee, Ling Liu, David Buttler |
| 2004 | ICSOC | Discovering and ranking web services with BASIL: a personalized approach with biased focus. | James Caverlee, Ling Liu, Daniel Rocco |