Research
Curriculum Vitae | Google Scholar | SSRN
Publications
Liu Liu, Daria Dzyabura, and Natalie Mizik (2020), "Visual Listening In: Extracting Brand Image Portrayed on Social Media," Marketing Science 39(4): 669-686.
- Lead article
- Featured in ISMS press release (August 6, 2020)
- Marketing Science Institute Working Paper Series 2020, Report No.20-113
- John D.C. Little Award Finalist, 2020
- Frank M. Bass Best Dissertation-Based Paper Award Finalist, 2020
- Dissertation Award from the Statistics in Marketing Section of the American Statistical Association, 2018
- John A. Howard/American Marketing Association Doctoral Dissertation Award Finalist, 2018
Linda Hagen, Kosuke Uetake, Nathan Yang, Bryan Bollinger, Allison Chaney, Daria Dzyabura, Jordan Etkin, Avi Goldfarb, Liu Liu, K. Sudhir, YanwenWang, JamesWright, and Ying Zhu (2020), "How Can Machine Learning Aid Behavioral Marketing Research?" Marketing Letters, 31(4), 361-370
Liu Liu, Daria Dzyabura, and Natalie Mizik (2018), "Visual Listening In: Extracting Brand Image Portrayed on Social Media," Proceedings of the Thirty-Second AAAI Conference on Articial Intelligence, February 2018 [peer-reviewed, non-archival]
Liu Liu, Jack Mostow, and Gregory Aist (2013), "Generating Example Contexts to Help Children Learn Word Meaning," Journal of Natural Language Engineering, 19.02: 187-212
Ni Lao, Jun Zhu, Liu Liu, Yandong Liu, and William W. Cohen (2010), "Efficient Relational Learning with Hidden Variable Detection," In Advances in Neural Information Processing Systems (NIPS) (pp. 1234-1242)
Jing Zhang, Jie Tang, Liu Liu, and Juanzi Li (2008), "A Mixture Model for Expert Finding," Advances in Knowledge Discovery and Data Mining, 466-478.
Working papers
"Collect Now, Consume Later: Modeling Consumer Collection Behavior on Digital Platforms," with Daria Dzyabura, under review at the Journal of Marketing Research
“Building Persuasive Stories with Emotion Sequences,” with Samsun Knight and Laura Kornish
- Draft accepted and presented at the North American Chapter of the Association for Computation Linguistics (NAACL) Workshop on Narrative Understanding [peer-reviewed, non-archival]
- Winner of Steven Shugan ``Best Junior Faculty Paper" award at the Artificial Intelligence in Management Conference (AIM) 2025
- Marketing Science Institute Working Paper Series 2025, Report No. 25-124
"An Affine-Subspace Shrinkage Approach to Choice-Based Conjoint Estimation," with Yupeng Chen and Qi Yu
Work in progress
“Generative AI for Psychological Research,” with Samsun Knight and Nick Reinholtz
“Visual Elicitation of Consumer Preference,” with Shane Wang
“Category Learning through Images: An Application to Movie Posters,” with Alix Barasch, Paul Blythe, Natasha Foutz, and Masakazu Ishihara