Data Science & Business Analytics Research Projects

Decoding Persuasion on Crowdfunding Platforms

QIAO Dandan

This research proposes a novel prediction framework based on persuasion theory to enhance crowdfunding success predictions. It aims to identify persuasive elements in project descriptions and improve the prediction accuracy so as to provide guidance for crowdfunding project initiators. The study integrates computational methods and deep learning to not only boost prediction performance but also offer interpretable insights, contributing to information systems and crowdfunding design.

Investigation on Digital Platforms and Human-machine Co-behavior Through AI, Empirical and Experimental Methods

SUN Chenshuo

This proposal investigates the impact of digital technologies on consumer behavior across e-commerce and social media platforms. Focusing on voice AI in shopping, filter bubbles in recommender systems, and social features affecting search volume, the project aims to provide valuable insights and address key questions in these domains.

• Machine Learning, Predictive Analytics

Understanding Online Contribution: Impact Evaluation and Crowd Wisdom Extraction

QIAO Dandan

With the massive amount of online contributions shaping individual and organizational decision-making, this project delves into utilizing and understanding this valuable resource. By combining econometrics and natural language processing, the research seeks innovative insights to leverage these vast information pools and assess their impacts on commerce and society.

• Big Data Analytics

Academic Integrity Post-COVID-19: Multimodal Online Assessment Cheating Detection

HAHN Jungpil

Cheating cases are on the rise in academia, especially during the shift to remote learning. Using a blend of user studies and machine learning (ML) with multimodal features, this project aims to develop a robust ML model for detecting and identifying cheating patterns in various online assessment contexts.

• Machine Learning

Quantifying the Impact of Privacy Technologies (PETs) on Firms

HAHN Jungpil

Consumers' adoption of privacy enhancing technologies creates data analytics challenges to firms that rely on data to support their business models. This project seeks to develop conceptual and methodological frameworks to quantify the impact that such technologies will have on firms' analytics capabilities and business value.

• Privacy and Ethics of Data Management