computational social science
Definition
Computational social science refers to the application of network psychometric methods to analyze large-scale communicative data, enabling systematic investigation of patterns in human expression and social phenomena. This approach integrates automated detection technologies such as facial expression recognition with computational modeling techniques to extract meaningful patterns from visual material in political contexts. Computational social science bridges traditional psychological methods with machine learning approaches, allowing researchers to examine complex dynamics such as emotion covariation across populations, offering new avenues for understanding affective dimensions of political communication.
Sources: Tomašević & Major (2024)
Related Terms
Applications
Computational Social Science and Emotional Dynamics
Computational social science enables systematic investigation of how emotions coevolve and vary over time in naturalistic settings such as political speeches, moving beyond static trait conceptualizations to examine the temporal unfolding and pattern formation of emotional expressions. By applying network psychometric methods to facial expression recognition data, computational approaches reveal the structure of relationships between different emotions and how these relationships vary across populations.
Sources: Tomašević & Major (2024)
Computational Social Science and Political Communication
Computational social science bridges the study of nonverbal communication in political contexts with network modeling and emotion analysis, providing insights into how political leaders structure their emotional expression during public performances. This integration of automated detection from video data with computational modeling reveals distinct patterns in affective communication.
Sources: Tomašević & Major (2024)
