# overview
My research broadly examines how people understand and communicate about health and illnesses and how such understanding and communication are enabled and constrained by social, political, cultural, and technological factors. My research is informed by the new paradigm of "big data" research, which marries the traditional interpretive and postpositive epistemologies to discover patterns of meanings and relationships in texts, videos, narratives, and social networks (interpretive epistemology) using scientific data processing methods developed in computer science and data science.

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3507 Strategy, Management And Organisational Behaviour

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35 Commerce, Management, Tourism And Services

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8.3 Policy, Ethics, And Research Governance

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8 Health And Social Care Services Research

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3 Prevention Of Disease And Conditions, And Promotion Of Well-being

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Networking And Information Technology R&d (nitrd)

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3 Prevention Of Disease And Conditions, And Promotion Of Well-being

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Peking University - (Beijing, Beijing, China)

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University of Southern California - (Los Angeles, California, United States)

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University of Southern California - (Los Angeles, California, United States)

# publications[].label
Evaluating Domain-Independent Small Talk Conversations to Improve Clinical Communication Interaction for Human and Machine

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Middle-Aged and Older African Americans' Information Use During the COVID-19 Pandemic: An Interview Study.

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An Interactive Game for Changing Youth Behavior Regarding E-cigarettes

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Texas Public Agencies Tweets and Public Engagement During the COVID-19 Pandemic: Natural Language Processing Approach (Preprint)

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Culture and health reporting: a comparative content analysis of newspapers in the United States and China.

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Understanding women's stories about drinking: implications for health interventions.

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What Do Social Media Influencers Say about Health? A Theory-Driven Content Analysis of Top Ten Health Influencers' Posts on Sina Weibo.

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"Down the Rabbit Hole" of Vaccine Misinformation on YouTube: Network Exposure Study

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Exploring the Early Adoption of Open AI among Laypeople and Technical Professionals: An Analysis of Twitter Conversations on #ChatGPT and #GPT3

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Cultural adaptation in HPV vaccine intervention among racial and ethical minority population: a systematic literature review.

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Health Information Consumption under COVID-19 Lockdown: An Interview Study of Residents of Hubei Province, China.

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Portrayals of Mental Illnesses in Womens and Mens Magazines in the United States

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The stigmatization of suicide: A study of stories told by college students in China.

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Social Media and the Public Sphere in China

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Experimenting with a Prototype Interactive Narrative Game to Improve Knowledge and Beliefs for the HPV Vaccine.

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What Causes Postpartum Depression and How to Cope with It: A Phenomenological Study of Mothers in China.

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Managing government legitimacy during the COVID-19 pandemic in China: a semantic network analysis of state-run media Sina Weibo posts

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Texas Public Agencies' Tweets and Public Engagement During the COVID-19 Pandemic: Natural Language Processing Approach.

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Postpartum Depression and Social Support in China: A Cultural Perspective.

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Narratives About Mental Illnesses in China: The Voices of Generation Y.

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An Integral Model of Collective Action in Organizations and Beyond

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Egyptian Newspapers Coverage of COVID-19 Vaccines: A Theoretically Driven Content Analysis.

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The spread of COVID-19 vaccine information in Arabic on YouTube: A network exposure study.

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Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models (Preprint)

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Corporate Social Responsibility Communication Through Corporate Websites

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Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models.

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Rise of Health Consumerism in China and Its Effects on Physicians' Professional Identity and the Physician-Patient Relationship and Communication.

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TV Advertising, Corporate Power, and Latino Health Disparities.

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Representation of autism in leading newspapers in china: a content analysis.

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Medical artificial intelligence ethics: A systematic review of empirical studies.

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How gay men's wives in China practice co-cultural communication: Culture, identity, and sensemaking

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Chinese gay mens coming out narratives: Connecting social relationship to co-cultural theory

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Sun Exposure, Tanning Beds, and Herbs That Cure: An Examination of Skin Cancer on Pinterest.

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Self-disclosure and received social support among women experiencing infertility on reddit: A natural language processing approach

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The CDC and State Health Department Facebook Messages: An Examination of Frames and the Extended Parallel Processing Model

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Understanding Public Perceptions of Measles from Twitter Using Multi-Task Convolutional Neural Networks.

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Be aware of superbugs: Newspaper coverage of NDM-1 in India, UK, and the USA

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Social media and outbreaks of emerging infectious diseases: A systematic review of literature.

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How colour and visual complexity affect the evaluation of skin cancer infographics: an experiment study.

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Effectiveness of health messages to change women's thin-ideal and unhealthy weight control intentions: Connecting social norms and social networks approaches

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Examining Potential Usability and Health Beliefs Among Young Adults Using a Conversational Agent for HPV Vaccine Counseling.

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Down the Rabbit Hole of Vaccine Misinformation on YouTube: Network Exposure Study (Preprint)

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PROMOTING CANCER SCREENING AMONG RURAL AFRICAN AMERICANS: A SOCIAL NETWORK APPROACH.

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All pins are not created equal: communicating skin cancer visually on Pinterest.

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Media Use During COVID-19: An Investigation of Negative Effects on the Mental Health of Asian Versus White Americans

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Communication studies of corporate social responsibility

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My Story of Depression: A Content Analysis of Autobiographic Videos on Douyin.

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The stigma of autism in china: an analysis of newspaper portrayals of autism between 2003 and 2012.

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Corporate social responsibility communication of Chinese and global corporations in China

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What Satisfies Parents of Pediatric Patients in China: A Grounded Theory Building Analysis of Online Physician Reviews.

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CRENO: An ontology to model concepts relating to culture, race, ethnicity, and nationality for health data.

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Examining Potential Usability and Health Beliefs Among Young Adults Using a Conversational Agent for HPV Vaccine Counseling

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Media discourse of corporate social responsibility in China: a content analysis of newspapers

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The Recreation of Gender Stereotypes in Male Cross-Dressing Performances on Douyin

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Exploring dialectical tensions for institutional maintenance: A case of google and its censored chinese search engine

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What do we believe in? Rumors and processing strategies during the COVID-19 outbreak in China.

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Measuring media-related health and mental health information acquisition among Latino adults in the United States.

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Using a Machine Learning Approach to Monitor COVID-19 Vaccine Adverse Events (VAE) from Twitter Data.

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Twitter message types, health beliefs, and vaccine attitudes during the 2015 measles outbreak in California.

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Sensemaking during a pandemic: A semantic network analysis of COVID-19 and vaccine-related discussion on Reddit

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'Picture me heart disease free': understanding African Americans' cardiovascular disease experiences through a culture-centered approach

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Tweeting about measles during stages of an outbreak: A semantic network approach to the framing of an emerging infectious disease.

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Tensions of Health: Narratives of Employee Wellness Program Participants.

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Unraveling Public Health Crises Across Stages: Understanding Twitter Emotions and Message Types During the California Measles Outbreak

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The representation of the Chinese product crisis in national and local newspapers in the United States

# streetAddress
Texas A&M University; Communication; 4234 TAMU

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Can Social Media Inform Public Health Efforts?

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Texas A&M communications experts reveals how to talk about COVID vaccines so people will listen

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New Texas A&M lab works to eliminate bias in artificial intelligence and machine learning