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Kunpeng Zhang

Associate Professor

University of Maryland at College Park

United States

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Kunpeng Zhang is an Associate Professor at the University of Maryland, College Park. His research areas include dynamic causal factors in non-stationary series, information diffusion, and prediction methodologies in venture capital networks. Recent publications highlight his focus on community search frameworks and the analysis of user-generated content on social media platforms.

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Collaborators (6)

Jennifer Jie Zhang

UNITED STATES

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Xu Teng

UNITED STATES

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Mikhail Lysyakov

Assistant Professor of Computers and Information Systems

University of Rochester

UNITED STATES

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Liangfei Qiu

Associate Professor

University of Florida

UNITED STATES

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Mirai Igarashi

Associate Professor

Osaka University

JAPAN

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Goce Trajcevski

Associate Professor

Iowa State University

UNITED STATES

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Kunpeng Zhang

Research Interests

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About

Articles (25)

Generalizing across non-stationary series via learning dynamic causal factors

Identifying Influential Users by Topic in Unstructured User-Generated Content

COMET: An Interactive Framework for Efficient and Effective Community Search via Active Learning

Help Me Screen: Analyzing and Predicting the Success of Start-ups in Dynamic Venture Capital Networks

Code and Data Repository for COMET: An Interactive Framework for Efficient and Effective Community Search via Active Learning

Disentangling Inter- and Intra-Cascades Dynamics for Information Diffusion Prediction

Retailer Differentiation in Social Media: An Investigation of Firm-Generated Content on Twitter

Divide and Contrast: A Text-Based Method for Firm Market Risk Prediction

Code and Data Repository for Divide-and-Contrast: A Text-based Method for Firm Market Risk Prediction

Inferring Real Mobility in Presence of Fake Check-ins Data

Score-based Graph Learning for Urban Flow Prediction

Information Cascade Popularity Prediction via Probabilistic Diffusion

A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability

Time to Stop? An Empirical Investigation on the Consequences of Canceling Monetary Incentives on a Digital Platform

CasFlow: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction

Adversarial Human Trajectory Learning for Trip Recommendation

Semi-Supervised Anomaly Detection Via Neural Process

sDTM: A Supervised Bayesian Deep Topic Model for Text Analytics

Counterfactual Graph Learning for Anomaly Detection on Attributed Networks

Pictures that are Worth a Thousand Donations: How Emotions in Project Images Drive the Success of Online Charity Fundraising Campaigns? An Image Design Perspective

Risk Disclosure in Crowdfunding

A Survey of Information Cascade Analysis

Analyzing Firm Reports for Volatility Prediction: A Knowledge-Driven Text-Embedding Approach

CCGL: Contrastive Cascade Graph Learning

CasFlow: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction

Collaborators (6)

Jennifer Jie Zhang

Xu Teng

Mikhail Lysyakov

Liangfei Qiu

Mirai Igarashi

Goce Trajcevski

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