Binxuan Huang
CASOS Student, CASOS, ISR

Email: binxuanh[AT]andrew.cmu.edu

Homepage: https://binxuan.github.io/

Advisor: Kathleen M. Carley

Office: Wean Hall 5111

Projects:

Publications:

Huang, Binxuan & Carley, Kathleen M . (2018-forthcoming). Location Order Recovery in Trails with Low Temporal Resolution. To appear in IEEE Transactions on Network Science and Engineering, IEEE.

Huang, Binxuan & Carley, Kathleen M . (2018-forthcoming). Parameterized Convolutional Neural Networks for Aspect Level Sentiment Classification. in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), ACL.

Huang, Binxuan & Ou, Yanglan & Carley, Kathleen M . (2018). Aspect level Sentiment Classification with Attention-over-Attention Neural Networks. In Proceedings of the 2018 SBP-BRiMS Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation, Washington, DC, June 10-13, 2018, Springer. [DOI] WebSite: [link]

Zhang, Yu & Wei, Wei & Huang, Binxuan & Carley, Kathleen M & Zhang, Yan. (2017). RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation. In Proceedings of 2017 ACM International Conference on Information and Knowledge Management (CIKM'17), Singapore, November 2017., [pdf]

Natali, Felicia & Carley, Kathleen M & Zhu, Feida & Huang, Binxuan. (2017). The role of different tie strength in disseminating different topics on a microblog. ASONAM '17: Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Sydney, Australia, July 31 - August 3. 203-207. Research Collection School Of Information Systems, WebSite: [link]

Huang, Binxuan & Carley, Kathleen M . (2017). On Predicting Geolocation of Tweets using Convolutional Neural Networks. In Proceedings of the International Conference Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2017); Dongwon Lee, YuRu Lin, Robert Thompson and Nathaniel Osgood (Eds.) July 5-8, 2017, Washington D.C., Springer. [pdf]

Frankenstein, William & Huang, Binxuan & Carley, Kathleen M . (2016). NATO Trident Juncture on Twitter: Public Discussion. Carnegie Mellon University School of Computer Science, Institute for Software Research, Technical Report CMU-ISR-16-100, [pdf]

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