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Huan Liu, Regents Professor
Computer Science and Engineering

School of Computing, and Augmented Intelligence

Ira A. Fulton Schools of Engineering, Arizona State University
PO Box 878809, Tempe, AZ 85287-8809, U.S.A.

Brickyard Suite 225 (SCAI), 699 South Mill Ave, Tempe, AZ 85281
for FedEx type mails

phone: 480-727-7349(voice) 480-965-2751(fax)
E-mail: huanliu at asu.edu or liuh.asu at gmail.com

Calendar

Free Download Textbook Social Media Mining: An Introduction Cambridge University Press, 2014 Chinese Translation, 2015 A Chinese Blog of Introduction

Data Mining and Machine Learning Lab

Social Computing Data

Feature Selection, scikit-feature Python repository

Social Computing, Behavioral-Cultural Modeling, and Prediction Series

ASU CSRankings

Office Location and Office Hours Brickyard 566 TTh 5:45 - 6:45PM Other times by appointment only Directions to CSE, SCAI Professional Activities, Keynotes, & Invited Talks	Classes in Fall 2024 CSE472 Social Media Mining TTh 4:30 PM - 5:45PM, HLMK (CAVC) 359 Line number: 69174, 8/22/2024 - 12/06/2024 (C) https://myasucourses.asu.edu CV Short Bio	Professional Memberships ACM (Fellow), AAAI (Fellow), AAAS (Fellow), IEEE (Fellow) ASEE, SIAM Editor in Chief ACM TIST, Frontiers in Big Data (Field) and DMM (Specialty)
Research Interests                                    New Surveys: 1. Causal Inference for Time Series Analysis: Problems, Methods, and Evaluation, 2. Socially Responsible AI Algorithms: Issues, Purposes, and Challenges 2021, 3. Causal Interpretability for Machine Learning - Problems, Methods and Evaluation 2020, 4. Learning Causality with Data: Problems and Methods 2020, 5. Privacy in Social Media: Identification, Mitigation and Applications, 2020; Frontiers in Big Data, Data Mining & Management His research focuses on developing computational methods for data mining, machine learning, and social computing, and designing efficient algorithms to enable effective problem solving ranging from basic research, text/Web mining, bioinformatics, image mining, to real-world applications. His work includes (i) dealing with high dimensional data via feature selection and feature discretization; (ii) social media mining/social computing, identifying the influentials in the blogosphere, group profiling and interaction; (iii) integrating multiple data sources to overcome ambiguity and uncertainty, (iv) employing domain knowledge for effective mining and information integration, and (v) assisting human experts by developing effective methods of ensemble learning, and active learning with hierarchical classification, subspace clustering, and meta data. Detailed information can be obtained via his publications and professional activities.  Associated with the AI lab at ASU; an affiliated faculty with Institute of Social Science Research at ASU
Graduate Students, Visiting Scholars, and Research Projects DMML Group Pictures Self motivated students looking for exciting projects can find more information here. Weekly lab meetings are held on Fridays. Related News Regents Professor is an AI Explorer of 4 Decades, ASU News Feb 8, 2023 An Algorithm to Detect Fake News: Q&A, ASU Knowledge Enterprise, July 13, 2020 Top ML Projects To Fight Fake News Fatigue During COVID-19 (FakeNewsTracker)  May, 2020 Data Driven Desease Modeling, FullCircle, FSE, ASU, May 26, 2020 ACM Member News, CACM, Feb 2020, Vol. 63, No. 2, page 17 Frontiers Science News, April 23, 2019 Following students to success, ASU NOW, Feburary 14, 2019 A non-compromising approach to privacy-preserving personalized services, KdNuggets, January 8, 2019 Algorithmic Detection of Fake News, Data Skeptic, September 10, 2018 The Data Defenders, ASU Now, March 27, 2018 (ASU Thrive Magazine, Spring 2018) A Quick Guide to Fake News Detection on Social Media, KDNuggets, Oct. 10, 2017, Most Shared Last Week, Blog in Chinese Measuring Topic Interpretability with Crowdsourcing, KDNuggets, Nov. 30, 2016 Mining Rich Data Types, KDD2016, August, 2016; Misinformation Key Terms, Explained, KDNuggets, August, 2016 scikit-feature, news blog, KDNuggets, 5 ML Projects MAP Essay on Information Filtering in Social Media During Disasters, June 23, 2016 When you'll protest on Twitter, India Times Tech ASU's TweetTracker helps make sense of social media data, November 25, 2015 Instant Understanding of Social Media Mining (Chinese), November 14, 2015 ``Challenges in Evaluating Big Social Media Data", April 13, 2015, Big Data and Data Analytical Platforms at ODBMS.org IEEERoundup, ``How to Mine Social Media", September 11, 2014 irevolution.net, Crowdsourcing Crisis Information, May 30, 2013 New Scientist, Finding Right Twitter Users in a Crisis, March 20, 2013 LifeWeek (SanLian ShengHuo ZhouKan), May 11, 2012 New Scientist, April 13, 2012 ReadWriteWeb, New Scientist, Toronto Star, August 2011, User Vulnerability in a Social Media Network
Software or Data Downloads FakeNewsNet - A Benchmark Data Repository for Fake News Detection on Social Media, Paper FakeNewsTracker - A Tool for Fake News Collection, Detection, and Visualization (Demo) TweetTracker (Demo) and TweetXplorer Demo scikit-feature, an open-source feature selection repository in Python, news blog, KDNuggets SlangDB - A Sentiment Dictionary for Slang Words ACT - a Social Media coordination platform for Humanitarian Assistance and Disaster Relief Social-Dimension Approach to Classification in Large-Scale Networks Group Structure and Evolution in Heterogeneous Network (Datasets and Information) Influential Bloggers (Dataset and Information) INTERACT for finding interacting features SCuBA for subspace clustering FCBF for feature selection Feature discretization RSVP (contact Alan "zheng.zhao at asu.edu" for installation and implementation details)
SBP-BRiMS2024 Tutorial on ``Defending against Generative AI Threats in NLP", September 19, 2024, CMU, Pittsburgh, PA KDD 2023 Tutorial on ``Socially Responsible Machine Learning: A Causal Perspective", August 2023, Long Beach, CA SDM 2023 Tutorial on ``Data-Efficient Graph Learning", April 28, 2023 Minneaplis, Minnesota SBP-BRiMS2022 Tutorial on ``Machine Learning for Causal Inference", September 20, CMU, Pittsburgh, PA KDD 2022 Tutorial on ``Toward Graph Minimally-Supervised Learning", August 16, 2022. DC SDM 2022 Tutorial on ``Socially Responsible AI for Data Mining: Theories and Practice", April 28-30, 2022. Alexandria, Virginia. Hybrid WSDM 2022 Tutorial on ``Graph Minimally-supervised Learning", February 21-25, 2022. Online SBP-BRiMS2021 Tutorial on ``Socially Responsible AI Algorithms: Issues, Purposes, and Challenges", July 6, 2021. Online. pdf ACM SIGKDD2019 Tutorial on ``Fake News Research: Theories, Detection Strategies, and Open Problems", August, 2019, Anchorage, Alaska. pdf ACM WSDM2019 Tutorial on Fake News: Fundamental Theories, Detection Strategies and Challenges, February 2019, Melbourne, Australia. pdf, media coverage IEEE ICDM2017 Tutorial on Mining Misinformation in Social Media: Understanding Its Rampant Spread, Harm, and Intervention, November 21, 2017, New Orleans, Louisiana. Slides SIGKDD2017 Tutorial on Recent Advances in Feature Selection: A Data Perspective, August 13, 2017, Halifax, Nova Scotia, Canada. pdf AAAI2017 Tutorial on Social Data Bias in Machine Learning: Impact, Evaluation, and Correction, February 4-5, 2017, San Francisco, CA. SBP2016 Tutorial on Misinformation on Social Media: Diffusion, Detection, and Intervention, June 28, 2016, Washington DC. Blog on KDnuggets ASONAM2015 Tutorial on Bot Detection in Social Media: Networks, Behavior, and Evaluation, August 25, 2015, Paris, France. DragonStar Lecture 2015 in Guilin on Data Mining and Some Advanced Topics July 9 - July 14, 2015 WWW2015 Tutorial on LIKE and Recommendation in Social Media (slides available) RecSys2014 Tutorial on Personalized Location Recommendation on Location Based Social Networks, slides SIGKDD14 Tutorial on Recommendation in Social Media - Recent Advances and New Frontiers, slides PAKDD2014 Tutorial on Mining Spammers in Social Media: Techniques and Applications, slides WWW2014 Tutorial on Trust in Social Computing, slides ICDM 2013 Tutorial on Social Media Mining: Fundamental Issues and Challenges, slides INFORMS 2012 Tutorial on Mining Social Media - A Brief Introduction, slides International Conference on Social Computing 2009 Tutorial on Community Detection and Behavior Prediction for Social Computing, ppt KDD08 Tutorial on Blogosphere: Research, Tools, and Applications, video SIAM Data Mining SDM 2007 Tutorial on Dimensionality Reduction for Data Mining - Techniques, Applications, and Trends AAAI 2005 Tutorial Notes on Downsizing Data for High Performance in Learning - Feature Selection Methods: pdf.zip
Call for Books, Chapters, Papers, or Nominations: Frontiers in Big Data, Data Mining and Management, How to Submit Call for Authors, Understanding AI: NLP, Causality, Fairness, and Ethics, A CRC Press book series Call for Papers, Elsevier Information Processing & Management - Special Issue on Dis/Misinformation Mining from Social Media, due on 1/20/2021, decision on 4/1/2021 Call for Papers, Springer Social Network Analysis and Mining (SNAM) - Special Issue on Tackling COVID-19 Infodemic, due Oct 2020, decision Dec 2020 Call for Papers, CIKM2020 MAISoN Workshop, Special Edition on Dis/Misinformation Mining from Social Media, Oct 20, 2020 Call for Chapters, ``Fake News, Disinformation, and Misinformation in Social Media - Emerging Research Challenges and Opportunities", Lecture Notes in Social Networks, Springer. to appear in early 2020 Call for Papers, IEEE Intelligent Systems: Special Issue on Non-IID Outlier Detection in Complex Contexts, 2019 due, 2020 to appear Call for Papers, ACM Journal DTRAP: Special Issue on Fake-News Research, 2019 due, 2020 to appear ACM CIKM 2019 Workshop on BigScholar2019, Beijing, China, November 2019 SDM2019 Workshop on ``FEND: Data Mining for FakE News in Social Media: Propagation, Detection and Mitigation", CFP (cancelled) IEEE Big Data 2018, CFP SIGKDD2018 Workshop on BigScholar2018, London, UK, August 2018 WWW2017 Workshop on BigScholar, Perth, Australia, April 2017 Feature Engineering for Machine Learning and Data Analytics, CRC, pdf Online Behavioral Analysis and Modeling, Janurary/February 2016, IEEE Intelligent Systems, Vol 31, Number 1 WWW2016 Workshop on BigScholar, Montreal, Canada, April 2016 BEAMS2015:  Behavior Analysis, Modeling, and Steering Workshop at ICDM2015, Call for Papers ASONAM2015, Paris, France. Call for Papers WWW2015 Workshop on BigScholar, Florence, Italy, 2015 SIGKDD2014 Doctoral Dissertation Award, Call for Nominations, deadline, April 30, 2014. CIKM2014 Workshops, Call for Proposals, deadline, April 20, 2014. WWW2014 Workshop on BigScholar, Call for Papers, Seoul, Korea. April 8, 2014. IEEE/CIC ICCC2014, Symposium on Social Networks and Big Data, Call for Papers, Shanghai, China. October 13-15, 2014 Springer Social Network Analysis and Mining,  Special Issue on "Uncovering Deception in Social Media", CFP, new due date: July 15, 2013. The 14th International Conference on Web-Age Information Management (WAIM'13), Beidaihe, China. June 14-16, 2013. SIAM International Conference on Data Mining (SDM'12), Disney’s Paradise Pier Hotel, Anaheim, CA. April 26-28, 2012. Poster in pdf SIAM International Conference on Data Mining (SDM'11), Mesa, Arizona. April 28 - 30, 2011. Photos and Blog by Dirk Van den Poel
Last updated on 5/3/2022