raushan zhandayeva

Does Affective Intelligence Theory Generalize? Evidence from the Russia-Ukraine War, under review

During international crises, domestic populations encounter competing strategic narratives that shape public understanding. Affective Intelligence Theory (AIT) suggests that anxiety disrupts habitual political thinking, prompting individuals to seek out more information, engage with a broader range of sources, and exhibit greater openness to counter-attitudinal perspectives. While well-supported in Western electoral contexts, its generalizability remains underexplored. This study tests AIT during an international crisis in Kazakhstan, where citizens confront competing narratives about Russia’s invasion of Ukraine. I field a preregistered online experiment (n = 649) with a validated anxiety induction and measure information behavior. The results show no significant effects of anxiety on these behaviors, challenging AIT’s assumptions. Despite successful anxiety induction, respondents did not seek more information, engage with diverse media, or reconsider prior attitudes. These results challenge the assumption that AIT’s core mechanisms apply universally, raising questions about the theory’s generalizability beyond Western electoral contexts.

The Ukraine Effect: Evolving Perceptions of Russia, China, and the West in Central Asia, with Hannah S. Chapman

This study examines how proximate conflicts shape public attitudes toward foreign countries. Using survey data from Kazakhstan and Kyrgyzstan collected both before and after Russia's 2022 invasion of Ukraine, we leverage this geopolitical shock to identify shifts in public sentiment toward major powers. We find that favorable views of Russia declined in both countries after the invasion, with Kazakhstan experiencing a more pronounced drop. This decline is primarily driven by titular ethnic groups. Economic ties through remittances and media usage showed limited influence on attitudes. While Russian media portrayed the United States as responsible for the conflict, attitudes toward the USA remained stable. Meanwhile, favorable views of China increased substantially, particularly in Kazakhstan where China surpassed Russia as the most positively viewed foreign power. These findings demonstrate how populations respond to conflicts that have significant domestic implications due to deep economic, cultural, and historical ties, contributing to our understanding of how international conflicts transform societies beyond immediate combatants.

Do Social Media News Feeds Affect Political Beliefs? Maybe Not, with Ethan Porter, Meet Daxini, Nina Ebensperger, Peng Wei, and Xiaoke Zhang

As traditional media has collapsed, more Americans than ever before report receiving their news via social media. This trend has sparked grave concern, in part on the assumption that social media news feeds drive a host of unwelcome outcomes, especially polarization and misinformation. Much existing research about the effects of social media news feeds, however, has been carried out in coordination with social media companies, leading to questions about research independence. To circumvent such concerns, we build and study a simulated, open-source version of a social media news feed. We focus on climate change, an issue often tied to polarization and misinformation. In a pre-registered experiment, we randomly vary the quality of climate change-related news that participants see in their simulated news feed. Despite the realistic nature of our news feed and ample statistical power, exposure to high-quality news feeds did not change attitudes.

Soft Power in Hard Times: Strategic Narratives and Public Opinion on the Russia-Ukraine War, with Adam Lenton

What shapes public attitudes towards foreign wars? While international relations scholarship has acknowledged the importance of narratives in shaping states’ strategic communications and behavior, we know less about how strategic narratives can influence domestic audiences’ attitudes towards foreign affairs, a gap which is especially relevant during major crises such as wars, when sharply diverging narratives compete for support and sympathy of foreign audiences. To address this gap, we consider public opinion towards the Russia-Ukraine War in India, presenting results from an original survey and survey-embedded experiment. Results suggest that different narrative content can influence attitudes towards interstate conflicts. Specifically, framing the conflict as an imperial war of conquest is associated with greater blame of Russia and less blame towards Ukraine, with these effects amplified when the narrative is communicated by an Indian messenger.

Human Mobility in Central Asia: Defining and Redefining Identity, forthcoming in Routledge Volume (2026)

Human mobility has always been integral to the Central Asian region, although recent scholarship understudies this phenomenon. This project provides a historic overview of human mobility in the region as well as its contemporary trends and challenges. While after the collapse of the Soviet Union, Central Asians were primarily going to Russia for economic opportunities, two recent shocks of the pandemic and the war in Ukraine might change these patterns. The War in Ukraine and subsequent inflow of Russians into the region brought up critical issues pertaining to national identity and belonging in hosting communities.

Anti-immigrant Attitudes in Russia: Understanding Determinants and Predicting Attitudes

Since the collapse of the Soviet Union, Russia has become a focal point of attraction for many labor migrants from the former Soviet republics. However, despite its empirical significance the case of Russia remains underinvestigated in the migration literature, especially with regard to public attitudes towards migrants. The existing research tends to overemphasize ethnicity as the primary driving determinant in anti-migrant sentiments. The research on sociotropic and material concerns continues to be siloed, making it hard to assess their relative importance in the Russian context. The paper attempts to investigate attitudes towards immigration in Russia and understand what might drive them using a range of unsupervised and supervised (parametric and nonparametric) machine learning algorithms. I also suggests further steps in pursuing this endeavor.

ANTI-IMMIGRANT ATTITUDES IN RUSSIA UNDERSTANDING DETERMINANTS.pdf