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Lina Zhou
Lina Zhou
Professor of Business Information Systems and Operations Management
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Contact

Lina Zhou, Ph.D.
Professor, BISOM
Professor, Data Science and Business Analytics
lzhou8@charlotte.edu

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Office: Friday 359
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9201 University City Blvd
Charlotte, NC 28223

Google Scholar

Lina Zhou

Research Updates

Modeling and Interpreting the Propagation Influence of Neighbor Information in Time-Variant Networks with Exemplification by Financial Risk Prediction. Journal of Management Information Systems.

Information Technology Internal Control Material Weaknesses in Financial Reporting: Categories, Trends, Associations, and Industry Effects. International Journal of Accounting Information Systems.

Depression Detection on Social Media: A Classification Framework and Research Challenges and Opportunities, Journal of Healthcare Informatics Research.

From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues. AIS Transactions on Human Computer Interaction.

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Research » Machine Learning and Text Mining

Machine Learning and Text Mining

Deep learning and machine Learning empower artificial intelligence, and artificial intelligence in turn augments human intelligence.

Selected Publications

Zhou, L., Rudin, C., Gombolay, M., Spohrer, J., Zhou, M., & Paul, S. (2023). From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues. AIS Transactions on Human Computer Interaction, 15(1).

Tao, J. L. Zhou, K. Hickey (2023). Making Sense of the Black-boxes: Toward Interpretable Text Classification using Deep Learning Models, Journal of the Association for Information Science and Technology. 74, 685-700.

Tao, J., X. Fang, and L. Zhou (2021), Unsupervised Deep Learning for Fake Content Detection in Social Media, Hawaii International Conference on System Sciences (HICSS-54). January 5-8, Kauai, HI, USA.

Zhou, L., Paul, S., Demirkan, H., Yuan, L., Spohrer, J., Zhou, M., & Basu, J. (2021). Intelligence Augmentation: Towards Building Human-Machine Symbiotic Relationship. AIS Transactions on Human Computer Interaction, 13(2), 243-264.

Zhou, L., S. Pan, J. Wang, and A.V. Vasilakos (2017), Machine Learning on Big Data: Opportunities and Challenges, Neurocomputing, 237, 350-361.

Kang, Y. and L. Zhou (2017), RubE: Rule-based Methods for Extracting Product Features from Online Consumer Reviews, Information & Management, 54(2), March, 166-176.

Narock, T., L. Zhou, and V. Yoon (2013). Semantic Similarity of Ontology Instances Using Polarity Mining. Journal of the Association for Information Science and Technology. 64(2), February, 416-427.

Li, S., L. Zhou, and Y. Li (2015). Improving Aspect Extraction by Augmenting a Frequency-Based Method with Web-based Similarity Measures. Information Processing and Management.51, 58-67.

Du, J. and L. Zhou (2012). Improving Financial Data Quality Using Ontologies. Decision Support Systems, 54, 76-86.

Chiang, W. Y., D. Zhang, and L. Zhou (2006). Predicting and Explaining Patronage Behavior toward Web and Traditional Stores Using Neural Networks: A Comparative Analysis with Logistic Regression. Decision Support Systems, 41, 514-531.

Zhang, D. and L. Zhou (2004). Discovering Golden Nuggets: Data Mining in Financial Applications. IEEE Transactions on Systems, Man, and Cybernetics: Part C, 34(4), 513-522.

Zhou, L. J. K. Burgoon, J. F. Nunamaker, and D. Twitchell (2004). Automated Linguistics Based Cues for Detecting Deception in Text-based Asynchronous Computer-Mediated Communication: An Empirical Investigation, Group Decision and Negotiation. 13(1), 81-106.

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