Dr.
Lu Tang’s Webpage
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Research Teaching Service CV
My
research examines how people understand and communicate about health and
illness and how such understanding and communication are enabled and
constrained by social, political, cultural, and technological factors. I am a
mixed-method researcher. My research is also informed by the new paradigm of “big data” research, which marries the
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.
Here are some of my ongoing and completed research studies.
AI Ethics
I
study ethics and biases in data science and artificial
intelligence (AI).
Our society
is on the cusp of a transition into a human-AI coexistence. Early evidence has
shown that decision-making based on big data and AI is plagued with biases.
Communication scholars are uniquely positioned to challenge the implicit biases
and assumptions embedded in models of natural language processing, deep
learning, and AI. I am the Director of the Data Justice Lab
received $300k from the Texas A&M Institute of Data Sciences to build a
truly interdisciplinary team with colleagues from Computer Science,
Visualization, Psychology, and Engineering to tackle issues related to data
science and social justice.
Recently,
I and colleagues (Dr.
Hwaryoung Seo at TAMU and
Dr. Sophia Fantus at UT Arlington) of the Data Justice Lab received an National Institute
of Health grant titled “Measuring
and Improving AI Alzheimer Researchers’ Knowledge, Attitudes and Practices of
AI Ethics.” In this study, we will develop the first scale to measure medical
AI researchers’ knowledge and attitudes toward ethical AI research. We will
also develop a virtual reality based educational program to teach AI developers
ethical principles and how to translate these ethical principles into
practices.
New Technologies to Promote HPV
Vaccination
Racial and ethnic minorities in the US face higher
risks of HPV and are less likely to benefit from HPV vaccines. Researchers have
tried to adapt promotion campaigns to different demographic groups with limited
success (For a systematic review of cultural adaptations in HPV vaccine campaigns
targeting racial and ethnic minority groups, see Zhang
& Tang, 2021). I have been studying how to use video games and chatbots
to engage audiences and promote HPV vaccination.
I am currently studying how to create an effective
chatbot to talk to young adults about HPV vaccination as a subcontract PI of a
grant from the Cancer Prevention and Research
Institute of Texas (PI: Dr. Cui Tao at UTHealth).
Social Media and Emerging Infectious
Diseases
EIDs
represent novel and uncertain risks and create unique challenges for the public
in understanding the diseases and adopting proper preventative behaviors. EIDs
also pose new questions to public health professionals and governmental
agencies regarding effectively communicating to the public about such risks. My
research is among the first in our field to examine EID-related social media
contents through a computational approach and makes unique contributions to
Health Communication and Crisis and Risk Communication studies
Using
novel machine learning, natural language processing (NLP), social network
analysis methods, as well as traditional content analysis, my research examines social media contents about EIDs
and EID outbreaks. These studies allow researchers to assess how the public
think and feel about EIDs as the outbreak emerges, develops, and disappears and
the models developed in these studies will allow researchers to analyze social
media contents about other EID outbreaks in real-time in the future. My earlier
study developed a convolutional neuro network model and classified over one
million tweets collected during the 2015 measles outbreak in terms of message
types, emotions, and vaccine attitudes. Governmental agencies such as the CDC
and state and local public health agencies shoulder special responsibilities in
effectively communicating with the public about EIDs. I also study how
governmental agencies communicate health and risk information to the public
using different social media. Recently, I used the latest AI-based natural
language processing technology (BERT) to identify the contents and
characteristics of the tweets published by state and local public health
departments in Texas about the COVID-19 pandemic and the relationship between
tweet contents and different types of public engagement (Tang
et al 2021).
The
velocity and impact of the spread of misinformation is another
characteristic of the information landscape about EIDs. My research examines
how misinformation spreads on social media and how people process such
misinformation. I studied how users are exposed to vaccine misinformation when
using YouTube by examining the recommendation networks based on YouTube’s
proprietary algorithm. This
study contributes to Diffusion of Innovation literature and demonstrates
the limited effects of YouTube’s ongoing efforts to curb the spread of
misinformation about vaccines and calls for a change in its recommendation
algorithm to combat the viral diffusion of vaccine misinformation. In addition
to studying the diffusion of misinformation on social media, my research also
examines how different demographic groups define and respond to misinformation
about EIDs. This line of research contributes to our understanding of the
spread of health misinformation and methods to fight it.
Culture, Minority Health and Health
Communication
How
culture influences people’s understanding of health, and their adoption of
different preventative behaviors has been my long-term research interest. I
study how different cultural groups understand health, diseases, and health
behaviors and explain such differences through a cultural lens. My research
focuses on the cultured understanding
of mental illness and stigma and how mental illness stigma is
historically, culturally, and politically situated and discursively
constructed. My research identifies the gendered stigma about autism,
postpartum depression, and general mental illness in China and alcoholism and
general mental illness the United States.
My
research also examines the health experiences
and communication of marginalized groups. Starting from a critical
perspective and a concern for voiceless groups, I combined critical theories
with innovative research methods such as the photovoice method to allow members
of underserved groups to express their views, share their experiences, and take
a leading role in identifying community-based solutions. This line of research
has been fueled by the enthusiasm of my doctoral students. For instance, by
asking African American individuals to take pictures about their experiences of
living with heart diseases and talk about these pictures, my study highlights
these individuals’ remarkable agency in leading a healthy lifestyle and
managing their heart diseases. Such agency is enabled and constrained by
structural determinants such as socioeconomic status, insurance,
discrimination, and knowledge (e.g. York
& Tang, 2021).
My
research also contributes to the understanding of how marginalized groups communicate with dominant groups by
utilizing and further developing the co-culture
theory, which is a
critical theory of intercultural communication. I studied how gay men in China
come out and how gay men’s wives communicate with their husbands and other
family members. These studies further developed the
co-culture theory by identifying new co-culture communication strategies and
further explaining the use of co-culture strategies at the intersection of
gender, sexual orientation, and culture (My two articles utilizing and further
developing the co-cultural theory: Bie & Tang, 2016; Tang,
Meadows, & Li, 2020).
Stigma, Gender and Health
Communication
Stigma
is another topic that I have investigated extensively. I have worked with my
former and current doctoral students on stigma associate with mental illness (Tang
& Bie, 2016), postpartum depression (Tang
et al. 2017; Tang
et al, 2020), autism (Tang
& Bie, 2015), and suicide (Zou
et al., 2021) in China.
My
work on mental illness stigma and minority health provides insights into the
causes of the under-utilization of mental health services among minority
populations and provides a roadmap for dispelling such stigma and promote
mental health among minority groups. I have recently been awarded a “Pioneering
Ideas: Exploring the Future to Build a Culture of Health” grant by the Robert Wood Johnson Foundation (as a co-I, Award #78359) to study Spanish media content about mental illness,
media use, and mental illness stigma among Latinx youth (PI: Dr.
Melissa Dopont-Reyes at Columbia). In this
project, we conduct a survey of diverse groups of Latinx youth to assess their
mental illness stigma and their media consumption patterns. We will also
analyze the content of Spanish-language mass media and social media related to
mental health using both content analysis and natural language processing.
