Rasmus W. Schmøkel

Rasmus W. Schmøkel
  • Ph.D-fellow at University of Southern Denmark

About

4
Publications
442
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72
Citations
Current institution
University of Southern Denmark
University of Southern Denmark
  • Department of Political Science and Public Management
  • Odense, Denmark
Current position
  • Ph.D-fellow

Publications

Publications (4)
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The journalistic preference for extreme exemplars: educational socialization, psychological biases, or editorial policy?
Article
  • Dec 2023
Exemplars are central in news reporting. However, extreme negative exemplars can bias citizens’ factual perceptions and attributions of political responsibility. Nonetheless, our knowledge of the factors shaping journalistic preferences for including exemplars in news stories is limited. We investigate the extent to which educational socialization,...
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Figure 1. Proportion of cross-platform and platform-specific candidate...
Figure 2. Time series of cross-platform candidate pictures relative to...
Figure 3. Emotion classifications per candidate and platform.
Overview of image posts, candidate pictures, and cross-platform...
Multiple binomial logistic regressions on post overperformance (DV) and...
Cross-Platform Emotions and Audience Engagement in Social Media Political Campaigning: Comparing Candidates’ Facebook and Instagram Images in the 2020 US Election
Article
Full-text available
  • Sep 2022
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;...
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Figure 1. Workflow for collecting, classifying, and hydrating emotions...
Figure 2. Examples of text variants in pixel-based deduplication.
Figure 3. K-means clustering example.
Figure 4. Pykognition image output with face boxes.
+1 Figure 5. Emotions for the promote category.
FBAdLibrarian and Pykognition: open science tools for the collection and emotion detection of images in Facebook political ads with computer vision
Article
Full-text available
  • May 2021
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...
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