Jingwen Zhang

Associate Professor

University of California, Davis

United States

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Jingwen Zhang is an Associate Professor at the University of California, Davis, USA. Her research interests include the application of artificial intelligence in health education, particularly focusing on women's awareness of heart health, social support dynamics in online settings, and the impact of misinformation on public health perceptions. Recent publications cover topics such as enhancing physical activity through AI chatbots and evaluating the effectiveness of misinformation interventions.

Articles (19)

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University of Pennsylvania

UNITED STATES

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Joshua Becker

Assitant Professor

UCL School of Management

UNITED KINGDOM

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Haoning Xue

Assistant Professor

University of Utah

UNITED STATES

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Lisa Miller

Professor

University of California, Davis

UNITED STATES

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Xiaoling Xiang

University of Michigan

UNITED STATES

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Jingwen Zhang

Research Interests

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Articles (19)

Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study

AI HeartBot to Increase Women's Awareness and Knowledge of Heart Attack: A Pilot Study (Preprint)

Human-Delivered Conversation versus AI Chatbot Conversation in Increasing Heart Attack Knowledge in Women in the United States: Quasi-Experimental Studies (Preprint)

Do syndemic conditions predict HIV medication adherence among urban African American men?

Author Correction: Prominent misinformation interventions reduce misperceptions but increase scepticism

Prominent misinformation interventions reduce misperceptions but increase scepticism

Interaction dynamics of social support expressions predict future support-seeking behaviors in online support groups

The majority of fact-checking labels in the United States are intense and this decreases engagement intention

Dialoging Resonance in Human-Chatbot Conversation: How Users Perceive and Reciprocate Recommendation Chatbot's Self-Disclosure Strategy

Conversational dynamics of joint attention and shared emotion predict outcomes in interpersonal influence situations: an interaction ritual perspective

Experimental evidence for structured information–sharing networks reducing medical errors

When national identity meets conspiracies: the contagion of national identity language in public engagement and discourse about COVID-19 conspiracy theories

Contradictory and complex health messages: an experimental test of different sources of uncertainty

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts

“I Do Not Trust Health Information Shared by My Parents”: Credibility Judgement of Health (Mis)information on Social Media in China

Analyzing Public Conversations About Heart Disease and Heart Health on Facebook From 2016 to 2021: Retrospective Observational Study Applying Latent Dirichlet Allocation Topic Modeling

Multiplicity and dynamics of social representations of the COVID-19 pandemic on Chinese social media from 2019 to 2020

When Media Health Stories Conflict: Test of the Contradictory Health Information Processing (CHIP) Model

The reduction of race and gender bias in clinical treatment recommendations using clinician peer networks in an experimental setting

Collaborators (13)

Wang Liao

Tomasz Gackowski

Yoo Jung Oh

Kaiping Chen

Bo Feng

Robert A. Bell

Cuihua Shen

Jingbo Meng

John B. Jemmott

Joshua Becker

Haoning Xue

Lisa Miller

Xiaoling Xiang

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