Hooked by Design: How Social Media Makes and Breaks Us

This thesis examines the evolving influence of social media platforms on user behavior, corporate engagement, and digital communication norms. Tracing the historical emergence of major platforms, it analyzes how psychological principles underlying attraction, engagement, and retention have been embedded within digital environments to shape user experiences. Drawing on case studies and international examples, the research highlights how cultural and economic factors — particularly in the United States — have influenced the adoption and monetization of social media. The study also explores broader shifts, including the rising commercialization of digital spaces and the evolving role of social media as both an information gateway and a tool for corporate reputation management. By connecting behavioral psychology with the strategic evolution of platform design and user interaction, the thesis offers new insights into how digital ecosystems mold consumer behavior and reshape global communication patterns

Creating an EV Supply Chain in Sub Saharan Africa: A Vehicle for Industrialization?

Sub-Saharan Africa (SSA) has long struggled to break out of economies defined by neo-colonialism and resource extractivism. The global energy transition and the buildout of electric vehicle (EV) fleets offers a unique opportunity for SSA to leverage its critical mineral reserves for industrialization. This paper seeks to buildout a working policy and economic framework to facilitate value addition in the EV supply chain. It first explores the status-quo of EV supply chain and SSA\u27s comparative advantages. It then explores successful case study nations -Chile, Indonesia and Morocco- as models of productive industrial policy. Finally, it adapts these policies to SSA in an attempt to create institutions and frameworks that will facilitate maximal value integration and addition

Regional Realignment: Mexico\u27s Appeal in the Era of Nearshoring

With growing geopolitical tensions and increased uncertainty over global trade, foreign companies are considering nearshoring (relocating their production to be closer to the end-market) and altering their supply chains to reduce risk and be more efficient. From growing demand for industrial parks to large public investments in Mexico’s manufacturing sector, evidence suggests that Mexico is one of the most attractive nearshoring locations. Therefore, using the process tracing method, in this thesis I explore why Mexico is such as compelling option for nearshoring. I find that Mexico’s strategic location, not only as a neighbor of the United States but its abundance in lithium and an isthmus, along with its multiple free trade agreements and investment incentives, make it an attractive option for companies looking to nearshore. The nearshoring discussion is relatively recent, having gained momentum since the COVID-19 Pandemic as multiple supply chain vulnerabilities were highlighted. Therefore, it is important to discuss nearshoring as its adoption and potential effects are and continue to unfold. This reconfiguration of supply chains entails new potential beneficiaries, like Mexico, and it is important to study nearshoring and its implications, not only in global trade dynamics but also domestically

Built to Last: Intergenerational Transfers and the Architecture of Inequality

This paper explores how altruistic motivations around bequests affect the distribution of wealth and consumption across generations. Using a two-period overlapping generations model with stochastic inheritance and distinct labor types, agents make decisions about consumption, savings, and bequests under CRRA utility. Altruism is modeled as a separate utility component, allowing the strength of intentional bequesting to vary across simulations. Simulation results show that altruism reduces within-group wealth inequality: both rich and poor agents exhibit tighter, less skewed wealth distributions. However, between-group inequality increases, as rich agents capture a larger share of total wealth. The net effect is a modest decline in overall wealth inequality, as measured by the Gini coefficient. Consumption inequality also falls slightly, driven by high-wealth agents reducing their consumption to leave larger bequests. Altruism amplifies the incentive to save rather than spend. Taken together, these findings show that altruism doesn’t uniformly reduce inequality, it redistributes it

How to Catch a Con: The Rhetorical Strategies of Fraudulent Political Leaders

The United States faces persistent challenges in controlling political fraud. Government agencies exhibit the second-highest fraud rate of any industry, and corruption levels have only worsened over the last decade, contributing to declining public trust in national leadership. Current fraud detection efforts generally catch late-stage, large-scale fraud, highlighting the need for earlier-detection mechanisms. One way this could be accomplished involves identifying rhetorical patterns that are commonly used by political frauds in order to flag high-risk individuals. Leaning on the Theory of Planned Behavior, it was hypothesized that political frauds would exhibit more rhetorical appeals to fear, blame, pathos, and self-promotion than non-frauds. To test this, a matched pairs design was employed, pairing six Congressional frauds with non-fraudulent counterparts. Five media appearances per politician were identified, transcribed, and coded (both deductively and inductively) using computer-aided text-analysis. ChatGPT Plus has been shown to be a fairly reliable coder of qualitative datasets (k = .66-.95) and thus was chosen. 18 rhetorical strategies were coded for raw instances per speaker, transformed into per-1,000-word frequencies, and analyzed with paired-samples t-tests. Results showed that fraudulent Congressmembers exhibited more combative, hyperbolic rhetoric, more national-level discourse, less measured policy discussion, and less local-level discourse than non-fraudulent Congressmembers. This supported our hypothesis and suggests that fraudulent political behavior may be commonly preceded by measurable linguistic patterns. Fraud-fighting agencies may benefit from using these insights to flag potentially fraudulent politicians earlier in their criminality

Priming Effects of Grammatical Gender on Gender Conceptualization in French

Several Indo-European languages have grammatical gender constructs in which nouns are assigned to a gendered noun class, typically masculine or feminine. Speakers of such languages must categorize inanimate nouns as masculine or feminine, despite these objects lacking biological sex. Some research has been conducted on whether grammatical gender affects the gender conceptualizations of inanimate objects: for example, do individuals perceive grammatically feminine objects as having more feminine qualities? The question of the effects of grammatical gender on cognition is rooted in the theory of linguistic relativity, first coined by Edward Sapir and Benjamin Whorf in the 1950s (Sera et al., 1994). This theory claims that cross-linguistic differences affect how speakers of different languages perceive reality. Research on linguistic relativity has explored several language constructs, including how different languages encode concepts of time, spatial orientation, color discrimination, number representations, and object categorization (Samuel et al., 2019). However, studies examining the effects of grammatical gender have yielded conflicting results, and often only focus on native speakers. This study examined the potential effects of priming with grammatical gender on conceptual gender associations in intermediate L2 French speakers. Participants were primed with images of inanimate nouns that were either grammatically masculine or feminine in French, then completed a lexical decision task in which target words represented culturally masculine or feminine activities. Results indicated little to no impact of grammatical gender on gender conceptualization. The findings of this study imply that grammatical gender may not affect gender concepts in non-fluent speakers of a gendered language, but the conflicting nature of the literature in this field calls for further research

Exploring Balanced Partitions in Triangular Lattices

This thesis investigates balanced partitions of spanning trees in triangular lattice graphs, extending previous work on grid graphs. The study of spanning tree partitions has applications in randomized algorithms and graph-based sampling techniques. First, we review foundational results on spanning trees in grid graphs, including probability bounds for obtaining balanced partitions when dividing a graph into two components. Then, we extend these methods to triangular lattices. Specifically, for a hexagonal region of a triangular lattice graph with a partition, we seek to establish a minimum probability that a randomly selected spanning tree can be divided into two balanced components. By adapting spanning tree distribution techniques, using a careful study of random walks, and employing combinatorial probability bounds, we provide theoretical guarantees for balanced partitions in triangular lattices. These results contribute to both theoretical graph analysis and practical applications in randomized algorithms and partition-based sampling methods. This research holds potential applications in redistricting electoral districts in the United States, equipping statisticians and political scientists with a framework for evaluating electoral boundary fairness

Fractured Simulacra: How Media Echo Chambers Shape Divergent Realities in Public Opinion

This thesis empirically investigates the relationship between exposure to time-varying partisan news content and individual policy attitudes. Combining individual-level Cooperative Election Study data (2020–2023, N≈68,000 for seven policy outcomes) with daily Fox News and MSNBC transcripts, I analyze how fluctuations in media narratives associate with public opinion. Leveraging large language models, I classify all relevant news segments by topic and ideological stance (liberal/conservative), generating daily time series of content volume and slant for each channel and policy issue. These series construct respondent-specific exposure measures based on self-reported viewership and 7-day rolling aggregates of media content preceding the survey interview date. OLS regression models predict standardized policy attitudes using interaction terms between viewership and media aggregates (Net Tone; or Volume and Slant simultaneously), controlling for demographics, ideology, party identification, and county and year fixed effects. The analysis finds a robust association between the ideological slant of recent media exposure and policy attitudes. Controlling for content volume and fixed effects, exposure to more liberal-slanted coverage in the preceding week significantly associates with holding more liberal views across nearly all policy domains (most p\u3c0.001). For instance, a one-unit increase in the normalized liberal slant (-1 to +1) of Fox News\u27 coverage of assault weapons over a week correlates with a 0.146 (SE=0.012) point increase in viewer support for a ban. This slant effect generally dominates the smaller and less consistent associations found for content volume. These findings demonstrate a strong correlation between how partisan outlets frame issues and viewer opinions, distinct from channel selection, highlighting the value of granular content analysis for understanding media\u27s role in shaping policy views

Find My Friends: Location-Sharing Ideologies and Peer Surveillance Practices

This thesis investigates the use of Find My Friends in the context of the Claremont Colleges. Students choose to location-share under initial rhetorical justifications of social reciprocity, and community-orientedness, and peer-safety. Drawing from ethnographic interviews conducted with users at the colleges, I argue that the infrastructure of Find My Friends in conjunction with the social and physical proximities of the Claremont environment creates a distinctive condition where users are subject to what I term as a “virtual, neoliberal, and participatory panopticon.” Here, users are seemingly empowered through the application’s neutralizing collapse of reciprocity and hierarchy that are seen in conventional surveillance structures. Instead, I suggest that Find My Friends disempowers its users as it reproduces the logics of surveillance on an interpersonal scale and invades the ways in which we move and interact within the social sphere

State Suspension vs. Termination of Medicaid on Recidivism Outcomes

This paper seeks to explore the relationship between Medicaid and recidivism through the lens of states suspending versus terminating Medicaid enrollment while an individual is incarcerated. Looking at post-ACA data from 2015, 2017, and 2018, and using a staggered difference-in-difference design, I find that suspension, rather than termination, reduces recidivism when interacted with Medicaid enrollment on a broad scale and among certain populations, including White non-Hispanics, individuals above 25 years old, and males. These findings suggest that policymakers should support more local operations, such as pre-release programs connecting individuals with Medicaid, in conjunction with suspending Medicaid on a statewide basis