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Voters’ Facial Expression Analysis as a Complement to Traditional Election Polls: Affective Voting in Spanish National Elections in 2023

Francisco Javier Otamendi et al.

Social Science Quarterly2026https://doi.org/10.1111/ssqu.70127article
ABDC B
Weight
0.50

What the paper says

ABSTRACT Objectives This research jointly combines voters. biometric facial expression analysis while viewing images of candidates and party logos with traditional surveys to define and quantify novel indicators of affective voting. The paper explains the innovative methodology and analyzes the results of the experiment carried out before the 2023 elections in Spain to understand how spontaneous emotional reactions to political stimuli explain the differences between electoral outcomes and polls. Results The results with a sample size of 305 subjects indicate that reactions to candidates' faces were triggered more often than those to logos and positive emotions were triggered less often than negative emotions. Affection due to above‐average positive reactions to candidates and disaffection generated by high levels of negativity partially explains the differences between outcomes and voting preferences. Conclusion The developed methods and tools open essential opportunities for analyzing electoral trends, designing surveys carried out by polling bodies and companies, and even designing electoral campaigns and selecting candidates by political parties.

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https://doi.org/https://doi.org/10.1111/ssqu.70127

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@article{francisco2026,
  title        = {{Voters’ Facial Expression Analysis as a Complement to Traditional Election Polls: Affective Voting in Spanish National Elections in 2023}},
  author       = {Francisco Javier Otamendi et al.},
  journal      = {Social Science Quarterly},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/ssqu.70127},
}

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Voters’ Facial Expression Analysis as a Complement to Traditional Election Polls: Affective Voting in Spanish National Elections in 2023

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.