معرفی
Nicholas Nicoletti is an Associate Professor of Political Science and Interim Director in the College of Business, Communication and Leadership at Alvernia University. He is also affiliated with the College of Humanities, Education and Social Sciences and contributes to sustainability initiatives at the institution.
His research centers on the interplay between domestic politics and international relations, particularly focusing on how moral reasoning influences political behavior. Key areas of inquiry include public opinion on war, citizen decision-making during wartime elections, and the role of media and elite cues in shaping beliefs. His methodological toolkit includes formal modeling, game theory, and experimental political science.
Dr. Nicoletti’s work integrates political psychology and causal inference, aiming to understand the cognitive and ethical dimensions of political choices. Though no publications are listed, his dissertation research on belief formation and wartime elections reflects a strong theoretical and empirical foundation.
He has contributed to interdisciplinary teaching and leadership, particularly in sustainability and political science education.
Dr. Nicoletti earned his Ph.D. in Political Science from the University at Buffalo (SUNY) in 2013. His doctoral research, titled Politicizing War: Information, Democracy, and Public Opinion, developed a formal model of citizen belief formation during wartime elections, incorporating signals from media and political elites. The study revealed how biased elite cues can dominate public perception, potentially leading to the election of opposition parties that terminate successful military campaigns.
He advises on academic programs and contributes to curriculum development, though specific advisees are not listed. There are no scientific awards mentioned in the available text.
He is associated with research in formal political theory and experimental design, particularly through his analysis of normative models and citizen decision-making under uncertainty.
