Anqi Shao
Biographic Data
| ID | 4267259 |
|---|---|
| NAME | Anqi Shao |
| GIVEN NAMES | Anqi |
| FAMILY NAME | Shao |
| SIGNATURE | SHAO A |
| AFFILIATIONS | University of Wisconsin–Madison |
| ORCID | 0000-0002-4051-2276 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 11 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
The human factor in AI governance
When AI Bots do not Follow Instructions
Constructing Vec-tionaries to Extract Message Features from Texts
While researchers often study message features like moral content in text, such as party manifestos and social media posts, their quantification remains a challenge. Conventional human coding struggles with scalability and intercoder reliability. While dictionary-based methods are cost-effective and computationally efficient, they often lack contextual sensitivity and are limited by the vocabularies developed for the original applications. In thi…
What does it mean to “do your own research?” A comparative content analysis of Dyor messages in Instagram and Facebook posts about reproductive health, food, and vaccines
Calls to “do your own research” (DYOR) on social media promote a range of claims, from expert-recommended treatments to conspiracy theories. Exploring how the slogan is used offers insight into how individuals navigate concerns about information accuracy in an abundant but low-trust media ecosystem. This quantitative content analysis investigates how DYOR messages in Facebook and Instagram posts about reproductive health, food and diet, and vacci…
Media Systems and Attention Cycles
We examined initial newspaper coverage of the COVID-19 outbreak (January–May 2020) in the United States and China, countries with contrasting media systems and pandemic experiences. We join the context-rich media systems literature and the longitudinal nature of the issue-attention literature to expand each by providing more system-level context for explaining how media cover an issue over time. U.S. coverage peaked later and stayed consistently …
Science Factionalism
Misinformation and intergroup bias are two pathologies challenging informed citizenship. This article examines how identity language is used in misinformation and debunking messages about controversial science on the Chinese digital public spheres and their impact on how the public engage with science. We collected an 8-year time series dataset of public discussion ( N = 6,039) on one of the most controversial science issues in China (GMO) from a…
A Mixed Methods Study of Public Perception of Social Distancing
In a rapidly changing public health crisis such as COVID-19, researchers need innovative approaches that can effectively link qualitative approaches and computational methods. In this article, computational and qualitative methods are used to analyze survey data collected in March 2020 ( n = 2,270) to explore the content of persuasive messages and their relationship with self-reported health behavior—that is, social distancing. Results suggest th…
Enhanced threat or therapeutic benefit? Risk and benefit perceptions of human gene editing by purpose and heritability of edits
Public discourse and deliberation are key to developing socially responsible and acceptable human gene editing research and applications. Researchers have raised concerns, however, that discourse about heritable gene edits, especially for non-therapeutic (or enhancement) purposes, might negatively bias public opinion of applications, including non-heritable edits to cure or prevent disease. Yet limited research exists examining how information ab…
A Mixed Methods Study of Public Perception of Social Distancing
In a rapidly changing public health crisis such as COVID-19, researchers need innovative approaches that can effectively link qualitative approaches and computational methods. In this article, computational and qualitative methods are used to analyze survey data collected in March 2020 ( n = 2,270) to explore the content of persuasive messages and their relationship with self-reported health behavior—that is, social distancing. Results suggest th…
Science Factionalism
Misinformation and intergroup bias are two pathologies challenging informed citizenship. This article examines how identity language is used in misinformation and debunking messages about controversial science on the Chinese digital public spheres and their impact on how the public engage with science. We collected an 8-year time series dataset of public discussion ( N = 6,039) on one of the most controversial science issues in China (GMO) from a…
Enhanced threat or therapeutic benefit? Risk and benefit perceptions of human gene editing by purpose and heritability of edits
Public discourse and deliberation are key to developing socially responsible and acceptable human gene editing research and applications. Researchers have raised concerns, however, that discourse about heritable gene edits, especially for non-therapeutic (or enhancement) purposes, might negatively bias public opinion of applications, including non-heritable edits to cure or prevent disease. Yet limited research exists examining how information ab…
Enhanced threat or therapeutic benefit? Risk and benefit perceptions of human gene editing by purpose and heritability of edits
Public discourse and deliberation are key to developing socially responsible and acceptable human gene editing research and applications. Researchers have raised concerns, however, that discourse about heritable gene edits, especially for non-therapeutic (or enhancement) purposes, might negatively bias public opinion of applications, including non-heritable edits to cure or prevent disease. Yet limited research exists examining how information ab…
A Mixed Methods Study of Public Perception of Social Distancing
In a rapidly changing public health crisis such as COVID-19, researchers need innovative approaches that can effectively link qualitative approaches and computational methods. In this article, computational and qualitative methods are used to analyze survey data collected in March 2020 ( n = 2,270) to explore the content of persuasive messages and their relationship with self-reported health behavior—that is, social distancing. Results suggest th…
Media Systems and Attention Cycles
We examined initial newspaper coverage of the COVID-19 outbreak (January–May 2020) in the United States and China, countries with contrasting media systems and pandemic experiences. We join the context-rich media systems literature and the longitudinal nature of the issue-attention literature to expand each by providing more system-level context for explaining how media cover an issue over time. U.S. coverage peaked later and stayed consistently …
Science Factionalism
Misinformation and intergroup bias are two pathologies challenging informed citizenship. This article examines how identity language is used in misinformation and debunking messages about controversial science on the Chinese digital public spheres and their impact on how the public engage with science. We collected an 8-year time series dataset of public discussion ( N = 6,039) on one of the most controversial science issues in China (GMO) from a…
What does it mean to “do your own research?” A comparative content analysis of Dyor messages in Instagram and Facebook posts about reproductive health, food, and vaccines
Calls to “do your own research” (DYOR) on social media promote a range of claims, from expert-recommended treatments to conspiracy theories. Exploring how the slogan is used offers insight into how individuals navigate concerns about information accuracy in an abundant but low-trust media ecosystem. This quantitative content analysis investigates how DYOR messages in Facebook and Instagram posts about reproductive health, food and diet, and vacci…
Constructing Vec-tionaries to Extract Message Features from Texts
While researchers often study message features like moral content in text, such as party manifestos and social media posts, their quantification remains a challenge. Conventional human coding struggles with scalability and intercoder reliability. While dictionary-based methods are cost-effective and computationally efficient, they often lack contextual sensitivity and are limited by the vocabularies developed for the original applications. In thi…
The human factor in AI governance
When AI Bots do not Follow Instructions
Psychology (5 works) · Computer Science (4 works) · Sociology (4 works) · Perception (3 works) · Political science (3 works) · Politics (3 works) · Advertising (2 works) · Business (2 works) · China (2 works) · Climate Change Communication and Perception (2 works)