Rasmus Schmøkel
Biographic Data
| ID | 4394181 |
|---|---|
| NAME | Rasmus Schmøkel |
| GIVEN NAMES | Rasmus |
| FAMILY NAME | Schmøkel |
| SIGNATURE | SCHMØKEL R |
| AFFILIATIONS | Digital Democracy Centre, University of Southern Denmark, Odense, Denmark |
| ORCID | 0000-0001-9558-4341 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 22 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 2 |
Cross-Platform Emotions and Audience Engagement in Social Media Political Campaigning
This study provides a cross-platform, longitudinal investigation of pictures depicting political candidates posted to Facebook and Instagram over a 15-month period during the 2020 US election(n = 4,977). After motivating an exploratory research design, we set out to expound: the extent of cross-platform image posting across Facebook and Instagram; the emotion expression of politicians across the two platforms; and the relationship between these e…
FBAdLibrarian and Pykognition
We present a methodological workflow using two open science tools that we developed. The first, FBAdLibrian, collects images from the Facebook Ad Library. The second, Pykognition, simplifies facial and emotion detection in images using computer vision. We provide a methodological workflow for using these tools and apply them to a case study of the 2020 US primary elections. We find that unique images of campaigning candidates are only a fraction …
Cross-Platform Emotions and Audience Engagement in Social Media Political Campaigning
This study provides a cross-platform, longitudinal investigation of pictures depicting political candidates posted to Facebook and Instagram over a 15-month period during the 2020 US election(n = 4,977). After motivating an exploratory research design, we set out to expound: the extent of cross-platform image posting across Facebook and Instagram; the emotion expression of politicians across the two platforms; and the relationship between these e…
FBAdLibrarian and Pykognition
We present a methodological workflow using two open science tools that we developed. The first, FBAdLibrian, collects images from the Facebook Ad Library. The second, Pykognition, simplifies facial and emotion detection in images using computer vision. We provide a methodological workflow for using these tools and apply them to a case study of the 2020 US primary elections. We find that unique images of campaigning candidates are only a fraction …
FBAdLibrarian and Pykognition
We present a methodological workflow using two open science tools that we developed. The first, FBAdLibrian, collects images from the Facebook Ad Library. The second, Pykognition, simplifies facial and emotion detection in images using computer vision. We provide a methodological workflow for using these tools and apply them to a case study of the 2020 US primary elections. We find that unique images of campaigning candidates are only a fraction …
Cross-Platform Emotions and Audience Engagement in Social Media Political Campaigning
This study provides a cross-platform, longitudinal investigation of pictures depicting political candidates posted to Facebook and Instagram over a 15-month period during the 2020 US election(n = 4,977). After motivating an exploratory research design, we set out to expound: the extent of cross-platform image posting across Facebook and Instagram; the emotion expression of politicians across the two platforms; and the relationship between these e…
Anger (2 works) · Computer Science (2 works) · Happiness (2 works) · Misinformation and Its Impacts (2 works) · Political science (2 works) · Politics (2 works) · Psychology (2 works) · Sadness (2 works) · Social Psychology (2 works) · Social Psychology (2 works)