Project Overview

This project is focused on highly-dynamic, ad-hoc crowd formation in emerging real-time socio-computational systems. While long-lived communities have been one of the key organizing principles of Web-based systems, these crowds are dynamically formed and potentially short-lived, often with only implicit signals of their formation and evolution. The goal of this research project is to develop the framework, algorithms, and systems for lightweight crowd-oriented search and computation so that stakeholders can distill high-quality information from bursty social systems and actively engage with the crowds generating this information.

Distilling high-quality information from bursty social systems and actively engaging with the crowds generating this information will result in improved real-time decision-making, impacting a wide range of stakeholders from areas such as epidemiology, law enforcement, government, finance, politics, among many others.

Publications

• Wei Niu, James Caverlee, and Haokai Lu. Neural Personalized Ranking for Image Recommendation. WSDM 2018.
• Wei Niu and James Caverlee. Location-Sensitive User Profiling Using Crowdsourced Labels. AAAI 2018.
• Cheng Cao, Hancheng Ge, James Caverlee, and Haokai Lu. What Are You Known For? Learning User Topical Profiles with Implicit and Explicit Footprints. SIGIR 2017.
• Wei Niu, Zhijiao Liu, and James Caverlee. On Local Expert Discovery via Geo-Located Crowds, Queries, and Candidates. ACM Transactions on Spatial Algorithms and Systems, Vol. 2, No. 4, 2016.
• Hancheng Ge and James Caverlee. College Towns, Vacation Spots, and Tech Hubs: Using Geo-Social Media to Model and Compare Locations. AAAI 2016.
• Hancheng Ge, James Caverlee, Nan Zhang, and Anna Squicciarini. Uncovering the Spatio-Temporal Dynamics of Memes in the Presence of Incomplete Information. CIKM 2016.
• Hancheng Ge, James Caverlee, and Haokai Lu. TAPER: A Contextual Tensor-Based Approach for Personalized Expert Recommendation. RecSys 2016.
• Haokai Lu, James Caverlee, and Wei Niu. Discovering What You’re Known For: A Contextual Poisson Factorization Approach. RecSys 2016.
• Wei Niu, James Caverlee, Haokai Lu, and Krishna Kamath. Community-based Geospatial Tag Estimation. ASONAM 2016.
• Wei Niu, Zhijiao Liu, and James Caverlee. LExL: A Learning Approach for Local Expert Discovery on Twitter (short paper). ECIR 2016.
• Haokai Lu and James Caverlee. Exploiting Geo-Spatial Preference for Personalized Expert Recommendation. ACM RecSys 2015.
• Haokai Lu, James Caverlee, and Wei Niu. BiasWatch: A Lightweight System for Discovering and Tracking Topic-Sensitive Opinion Bias in Social Media. CIKM 2015.
• Hancheng Ge, James Caverlee, and Kyumin Lee. Crowds, Gigs, and Super Sellers: A Mea- surement Study of a Supply-Driven Crowdsourcing Marketplace. ICWSM 2015.
• Yuan Liang, James Caverlee, and Cheng Cao. A Noise-Filtering Approach for Spatio-Temporal Event Detection in Social Media. ECIR 2015.
• Zhiyuan Cheng, James Caverlee, Vandana Bachani, and Himanshu Barthwal. Who is the Barbecue King of Texas? A Geo-Spatial Approach to Finding Local Experts. ACM SIGIR 2014.
• Krishna Y. Kamath and James Caverlee. Spatio-Temporal Meme Prediction: Learning What Hashtags Will Be Popular Where. Proceedings of the 22nd International Conference on Information and Knowledge Management (CIKM 2013).
• Jeffrey McGee, James Caverlee, and Zhiyuan Cheng. Location Prediction in Social Media Based on Tie Strength. Proceedings of the 22nd International Conference on Information and Knowledge Management (CIKM 2013).
• James Caverlee, Zhiyuan Cheng, Daniel Z. Sui, and Krishna Y. Kamath. Towards Geo-Social Intelligence: Mining, Analyzing, and Leveraging Geospatial Footprints in Social Media. Invited paper in the September 2013 issue of the IEEE Data Engineering Bulletin: Social Media and Data Analysis.
• Kyumin Lee, Krishna Y. Kamath, and James Caverlee. Combating Threats to Collective Attention in Social Media: An Evaluation, Proceedings of 7th International AAAI Conference on Weblogs and Social Media (ICWSM 2013).
• Krishna Y. Kamath, James Caverlee, Kyumin Lee, and Zhiyuan Cheng. Spatio-Temporal Dynamics of Online Memes: A Study of Geo-Tagged Tweets. Proceedings of the 22nd International World Wide Web Conference (WWW 2013).
• Yuan Liang, James Caverlee, Zhiyuan Cheng, and Krishna Y. Kamath. How Big is the Crowd? Event and Location Based Population Modeling in Social Media (best paper nominee). Proceedings of the 24th ACM Conference on Hypertext and Social Media (HT 2013).
• Krishna Y. Kamath and James Caverlee. Content-Based Crowd Retrieval on the Real-Time Web, Proceedings of 21st International Conference on Information and Knowledge Management (CIKM 2012).
• Krishna Y. Kamath, James Caverlee, Daniel Sui and Zhiyuan Cheng. Spatial Influence vs. Community Influence: Modeling the Global Spread of Social Media, Proceedings of 21st International Conference on Information and Knowledge Management (CIKM 2012).
• James Caverlee, Zhiyuan Cheng, Wai Gen Yee, Roger Liew, and Yuan Liang. Public Checkins versus Private Queries: Measuring and Evaluating Spatial Preference, Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN 2012).

Participants

• James Caverlee, PI

Project Alumni

• Cheng Cao (PhD 2017)
• Hancheng Ge (PhD 2017)
• Haokai Lu (PhD 2017)
• Wei Niu (PhD 2017)
• Jared Russell (Undergrad 20XX)
• Nazif Ali (Undergrad 20XX)
• Zhiyuan Cheng (PhD 2014)
• Krishna Kamath (PhD 2013)
• Zhijiao Liu (MS 2015)
• Himanshu Barthwal (MS 2015)
• Sindhuja Venkatash (MS 2014)
• Vandana Bachini (MS 2013)
• Yuan Liang (MS 2013)
• Jeff McGee (MS 2013)
• Aaron Moore
• Davis Land
• Jason Bolden, NSF REU Summer 2012, (BS with Honors, 2013)
• Kalil Armstrong NSF REU Summer 2012

Education and Outreach

• Elements of the research project have been incorporated into topics and projects in the undergraduate and graduate information retrieval courses (CSCE 470, CSCE 670) and a new data science course (CSCE 489).
• REU Students Jason Bolden (pic, pic) and Kalil Armstrong (pic) participated in the 2012 end-of-summer Texas A&M Summer REU research workshop. Jason Bolden ultimately finished his undergraduate thesis on aspects of this project as part of the Undergraduate Research Scholars Program.
• Hour-long "mini-tutorial" to 41 elementary school children from Dunbar Elementary (Lufkin ISD), January 29, 2013 Local NBC Coverage
• Two talks to visiting students from Jimmy Carter Early College High School (La Joya ISD) November 29, 2012 (~30 students) and November 21, 2013 (~50 students)
• The Power of Social Media, Feature in TAMU Engineering Magazine (2012 issue)
• Invited talks at Texas State (San Marcos)'s REU Program (July 12, 2012 and July 25, 2013), Houghton College (April 16, 2013), Penn State University (May 9, 2013), CollaborateCom Panel Discussion (October 22, 2013), USAA TechX (October 25, 2013), and KredibleNet Workshop on Reputation, Trust, and Authority at Stanford (October 18, 2013).
• Coding Gig Hackathon. First event: October 13, 2012; Second event: September 6, 2013.

This material is based upon work supported by the National Science Foundation under Grant Number IIS-1149383. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.