David M Goldberg
Biographic Data
| ID | 1322602 |
|---|---|
| NAME | David M Goldberg |
| GIVEN NAMES | David M |
| FAMILY NAME | Goldberg |
| SIGNATURE | GOLDBERG D M |
| AFFILIATIONS | San Diego State University |
| ORCID | 0000-0003-2617-5143 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1982 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
From reviews to risk assessment
Businesses and regulators benefit from rapidly detecting, categorizing, and prioritizing injury narratives across product categories. Online reviews are a valuable data source for identifying such narratives, but the challenge lies in extracting the most useful information from the enormous volume of data. In this study, we discover and categorize injury reports in online reviews using key terms prevalent in subcategories of injury narratives. We…
More than meets the eye
This study aims to address quality concerns in mobile Extended Reality (XR) apps by developing tools to classify user reviews from the Google Play Store. Our first major contribution is a holistic approach to coding thousands of reviews, offering a unified framework to assess feature concerns and feature suggestions, thereby enhancing the understanding of user expectations. We also introduce a novel toolset for extracting key terms related to the…
Gender and the Algorithmic Future
Cheating or Competing? University Students’ Experience of AI Marketing and What It Means for AI Literacy Programming
Given generative AI's rapid incursion into higher education, we examined how AI tools are marketed to US college students and how students experience AI promotions. Using a scalable action research model, we collected and analyzed 131 social media ads, 48 student interviews, and field notes compiled by three interns at student‐facing AI companies. Interviewees described AI use as a practical necessity shaped by grading systems, peer norms, and AI…
Bringing safety analytics to the online shopper
Purpose The widespread adoption of online purchasing has prompted increasing concerns about product safety, and regulators are beginning to hold e-commerce sites accountable for dangerous product defects. For online consumers, understanding the many inherent safety risks among the extensive array of products they browse is a formidable task. The authors attempt to address this problem via a client-side software artifact that warns shoppers about …
Safeguarding Korean Export Trade through Social Media-Driven Risk Identification and Characterization
Purpose – Korean exports account for a vast proportion of Korean GDP, and large volumes of Korean products are sold in the United States. Identifying and characterizing actual and potential product hazards related to Korean products is critical to safeguard Korean export trade, as severe quality issues can impair Korea’s reputation and reduce global consumer confidence in Korean products. In this study, we develop country-of-origin-based product …
Flexion and Skewness in Map Projections of the Earth
Tissot indicatrices have provided visual measures of local area and isotropy distortions. Here we show how large-scale distortions of flexion (bending) and skewness (lopsidedness) can be measured. Area and isotropy distortions depend on the map-projection metric; flexion and skewness, which manifest themselves on continental scales, depend on the first derivatives of the metric. We introduce new indicatrices that show not only area and isotropy d…
Discriminant Function Analysis
Cheating or Competing? University Students’ Experience of AI Marketing and What It Means for AI Literacy Programming
Given generative AI's rapid incursion into higher education, we examined how AI tools are marketed to US college students and how students experience AI promotions. Using a scalable action research model, we collected and analyzed 131 social media ads, 48 student interviews, and field notes compiled by three interns at student‐facing AI companies. Interviewees described AI use as a practical necessity shaped by grading systems, peer norms, and AI…
Discriminant Function Analysis
Flexion and Skewness in Map Projections of the Earth
Tissot indicatrices have provided visual measures of local area and isotropy distortions. Here we show how large-scale distortions of flexion (bending) and skewness (lopsidedness) can be measured. Area and isotropy distortions depend on the map-projection metric; flexion and skewness, which manifest themselves on continental scales, depend on the first derivatives of the metric. We introduce new indicatrices that show not only area and isotropy d…
Safeguarding Korean Export Trade through Social Media-Driven Risk Identification and Characterization
Purpose – Korean exports account for a vast proportion of Korean GDP, and large volumes of Korean products are sold in the United States. Identifying and characterizing actual and potential product hazards related to Korean products is critical to safeguard Korean export trade, as severe quality issues can impair Korea’s reputation and reduce global consumer confidence in Korean products. In this study, we develop country-of-origin-based product …
Bringing safety analytics to the online shopper
Purpose The widespread adoption of online purchasing has prompted increasing concerns about product safety, and regulators are beginning to hold e-commerce sites accountable for dangerous product defects. For online consumers, understanding the many inherent safety risks among the extensive array of products they browse is a formidable task. The authors attempt to address this problem via a client-side software artifact that warns shoppers about …
More than meets the eye
This study aims to address quality concerns in mobile Extended Reality (XR) apps by developing tools to classify user reviews from the Google Play Store. Our first major contribution is a holistic approach to coding thousands of reviews, offering a unified framework to assess feature concerns and feature suggestions, thereby enhancing the understanding of user expectations. We also introduce a novel toolset for extracting key terms related to the…
Gender and the Algorithmic Future
Cheating or Competing? University Students’ Experience of AI Marketing and What It Means for AI Literacy Programming
Given generative AI's rapid incursion into higher education, we examined how AI tools are marketed to US college students and how students experience AI promotions. Using a scalable action research model, we collected and analyzed 131 social media ads, 48 student interviews, and field notes compiled by three interns at student‐facing AI companies. Interviewees described AI use as a practical necessity shaped by grading systems, peer norms, and AI…
From reviews to risk assessment
Businesses and regulators benefit from rapidly detecting, categorizing, and prioritizing injury narratives across product categories. Online reviews are a valuable data source for identifying such narratives, but the challenge lies in extracting the most useful information from the enormous volume of data. In this study, we discover and categorize injury reports in online reviews using key terms prevalent in subcategories of injury narratives. We…
Computer Science (4 works) · Psychology (3 works) · Business (2 works) · Ethics and Social Impacts of AI (2 works) · Higher education (2 works) · Marketing (2 works) · Mathematics (2 works) · Originality (2 works) · Product (mathematics (2 works) · Social media (2 works)