Gizem Korkmaz
Papers
1
Total Citations
19
H-Index
1
About
Gizem Korkmaz is a pioneering computational social scientist whose research bridges generative modeling, human behavior, and social interaction dynamics. Her most influential work, "Generative Modeling of Human Behavior and Social Interactions Using Abductive Analysis" (2018, 19 citations), introduces a novel framework that applies abductive reasoning—an inference method that identifies the most plausible explanations for observed phenomena—to the study of human behavior. While abduction has been successfully used in fields like robotics and genetics, Korkmaz is among the first to adapt it for social science, enabling researchers to iteratively generate and refine models of complex social processes. This contribution offers a powerful alternative to purely deductive or inductive approaches, allowing for deeper causal insights into how individuals and groups interact. Her work has significant implications for understanding collective behavior, opinion dynamics, and social network evolution. By integrating computational methods with social theory, Korkmaz is shaping a new generation of data-driven social science. Her research stands out for its methodological rigor and interdisciplinary reach, making her a key figure in advancing how we model and interpret human social systems.
Research Focus
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Top Papers
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