TY - GEN
T1 - Understanding Political Communication Styles in Televised Debates via Body Movements
AU - Kang, Zhiqi
AU - Indudhara, Christina
AU - Mahorker, Kaushik
AU - Bucy, Erik P.
AU - Joo, Jungseock
N1 - Funding Information:
This work was supported by NSF SBE-SMA #1831848.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - Televised political debates have received much attention by scholars in political communication and social psychology who study nonverbal cues in interpersonal communication and their impact on candidate evaluations. An abundance of political multimedia and new platforms have required leaders to develop an effective and unique communication “style” which may rely on nonverbal devices such as face and body. Emotions conveyed by expressive gestures of candidates during debates have been shown to elicit stronger reactions from the public than rhetorical statements alone. Candidates, for example, may exploit assertive and aggressive gestures to communicate their confidence and attract supporters. Existing studies, however, are based largely on manual coding of human gestures, which may not be scalable or reproducible. The main objectives of our paper are to investigate the role of body movements of candidates using a systematic and automated approach as well as understand the context and effects of gestures. For this analysis, we collected a dataset of political debate videos from the 2020 Democratic presidential primaries and analyzed facial expressions and gestures of candidates. Our preliminary analysis demonstrates that candidates employ gestures to varying extents, and the amount of body movement is correlated with emotions conveyed in the candidates’ facial expressions. We discuss our dataset, preliminary results, and future directions in the following sections.
AB - Televised political debates have received much attention by scholars in political communication and social psychology who study nonverbal cues in interpersonal communication and their impact on candidate evaluations. An abundance of political multimedia and new platforms have required leaders to develop an effective and unique communication “style” which may rely on nonverbal devices such as face and body. Emotions conveyed by expressive gestures of candidates during debates have been shown to elicit stronger reactions from the public than rhetorical statements alone. Candidates, for example, may exploit assertive and aggressive gestures to communicate their confidence and attract supporters. Existing studies, however, are based largely on manual coding of human gestures, which may not be scalable or reproducible. The main objectives of our paper are to investigate the role of body movements of candidates using a systematic and automated approach as well as understand the context and effects of gestures. For this analysis, we collected a dataset of political debate videos from the 2020 Democratic presidential primaries and analyzed facial expressions and gestures of candidates. Our preliminary analysis demonstrates that candidates employ gestures to varying extents, and the amount of body movement is correlated with emotions conveyed in the candidates’ facial expressions. We discuss our dataset, preliminary results, and future directions in the following sections.
UR - http://www.scopus.com/inward/record.url?scp=85101396964&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-66415-2_55
DO - 10.1007/978-3-030-66415-2_55
M3 - Conference contribution
AN - SCOPUS:85101396964
SN - 9783030664145
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 788
EP - 793
BT - Computer Vision – ECCV 2020 Workshops, Proceedings
A2 - Bartoli, Adrien
A2 - Fusiello, Andrea
PB - Springer Science and Business Media Deutschland GmbH
T2 - Workshops held at the 16th European Conference on Computer Vision, ECCV 2020
Y2 - 23 August 2020 through 28 August 2020
ER -