Neil Talbert
Biographic Data
| ID | 4430287 |
|---|---|
| NAME | Neil Talbert |
| GIVEN NAMES | Neil |
| FAMILY NAME | Talbert |
| SIGNATURE | TALBERT N |
| AFFILIATIONS | University of Oklahoma |
| ORCID | 0009-0004-9300-9561 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Efficient Duplicate Comment Detection for Rulemaking Agencies With Unsupervised Deep Learning
Government agencies tasked with soliciting comments from the American public in response to changes in rulemaking have long been interested in finding effective techniques to automatically process spam comments, including flagging and filtering duplicate comments. Duplicate submissions are problematic because they obscure genuine public input and may amplify fringe opinions nonrepresentative of the majority of the American public. Given that dupl…
In Whom We Trust
As COVID-19 vaccination hesitancy remains a major public health issue, understanding the factors influencing attitudes and COVID-19 vaccination intentions is a public health priority. Applying the theory of planned behavior (TPB), this study examined the role of two forms of social trust – namely, particularized trust toward relationally close others and generalized trust toward people in general – in moderating the relationship between social no…
Public Segmentation and the Impact of AI Use in E-Rulemaking
Digitization has profoundly changed how government interacts with its publics. The expanding use of AI promises even more advancement. However, the rollout of AI is not without risk. This work explores the use of AI in federal rulemaking, the process by which regulations are introduced and revised. The US federal government has created digital platforms that dramatically expand access for the public commenting on pending regulations. However, the…
Managing Opinion Spamming with AI in Regulatory Public Engagement
Inoculating Against Anti-Vaccination Conspiracies
This study examined the efficacy of inoculation treatments in preventing anti-vaccination propaganda. Study predictions were tested in an independent-group experiment (N = 165), wherein participants were randomly assigned to a fact-based inoculation or a logic-based inoculation or a control message, with an excerpt from an anti-vaccination conspiracy film, Vaxxed, used as a counterattitudinal attack message. The results indicated that both inocul…
Inoculating Against Anti-Vaccination Conspiracies
This study examined the efficacy of inoculation treatments in preventing anti-vaccination propaganda. Study predictions were tested in an independent-group experiment (N = 165), wherein participants were randomly assigned to a fact-based inoculation or a logic-based inoculation or a control message, with an excerpt from an anti-vaccination conspiracy film, Vaxxed, used as a counterattitudinal attack message. The results indicated that both inocul…
Efficient Duplicate Comment Detection for Rulemaking Agencies With Unsupervised Deep Learning
Government agencies tasked with soliciting comments from the American public in response to changes in rulemaking have long been interested in finding effective techniques to automatically process spam comments, including flagging and filtering duplicate comments. Duplicate submissions are problematic because they obscure genuine public input and may amplify fringe opinions nonrepresentative of the majority of the American public. Given that dupl…
In Whom We Trust
As COVID-19 vaccination hesitancy remains a major public health issue, understanding the factors influencing attitudes and COVID-19 vaccination intentions is a public health priority. Applying the theory of planned behavior (TPB), this study examined the role of two forms of social trust – namely, particularized trust toward relationally close others and generalized trust toward people in general – in moderating the relationship between social no…
Public Segmentation and the Impact of AI Use in E-Rulemaking
Digitization has profoundly changed how government interacts with its publics. The expanding use of AI promises even more advancement. However, the rollout of AI is not without risk. This work explores the use of AI in federal rulemaking, the process by which regulations are introduced and revised. The US federal government has created digital platforms that dramatically expand access for the public commenting on pending regulations. However, the…
Managing Opinion Spamming with AI in Regulatory Public Engagement
Computer Science (3 works) · Law (3 works) · Political science (3 works) · Artificial Intelligence (2 works) · Hate Speech and Cyberbullying Detection (2 works) · Medicine (2 works) · Misinformation and Its Impacts (2 works) · Rulemaking (2 works) · Vaccination (2 works) · Vaccine Coverage and Hesitancy (2 works)