Developing Quantitative Methodologies for the Digital Humanities: A Case Study of 20th Century American Commentary on Russian Literature

Using scientific methods in the humanities is at the forefront of objective literary analysis. However, processing big data is particularly complex when the subject matter is qualitative rather than numerical. Large volumes of text require specialized tools to produce quantifiable data from ideas and sentiments. Our team researched the extent to which tools such as Weka and MALLET can test hypotheses about qualitative information. We examined the claim that literary commentary exists within political environments and used US periodical articles concerning Russian literature in the early twentieth century as a case study. These tools generated useful quantitative data that allowed us to run stepwise binary logistic regressions. These statistical tests allowed for time series experiments using sea change and emergency models of history, as well as classification experiments with regard to author characteristics, social issues, and sentiment expressed. Both types of experiments supported our claim with varying degrees, but more importantly served as a definitive demonstration that digitally enhanced quantitative forms of analysis can apply to qualitative data. Our findings set the foundation for further experiments in the emerging field of digital humanities.

Economic Development of Urban Areas

In this dissertation I study the development of urban areas. At the aggregate level I investigate how they may be affected by climate change policies and by being designated the seat of governmental power. At the household level I study with coauthors how microfinance could improve the health of urban residents. In Chapter 1, I investigate how local employment may be affected by electricity price increases, which is a likely consequence of climate change policies. I outline how previous studies that find large, negative effects may be biased. To overcome these biases I develop a novel estimation strategy that blends border-pair regressions with the synthetic control methodology. I show the conditions for consistent estimation. Using this estimator, I find no effect of contemporaneous price changes on employment. Consistent with the longer time-frame for manufacturing decisions, I do find evidence for negative effects from perceived permanent price shocks. These estimates are much smaller than previous research has found. National capital cities are often substantially larger than other cities in their countries. In Chapter 2, I investigate whether there is a causal effect from being a capital by studying the 1960 relocation of the Brazilian capital from Rio de Janeiro to Brasília. Using a synthetic controls strategy I find that losing the capital had no significant effects on Rio de Janeiro in terms of population, employment, or gross domestic product (GDP). I find that Brasília experienced large and significant increases in population, employment, and GDP. I find evidence of large spillovers from the public to the private sector. Chapter 3 investigates how microfinance could increase the uptake of costly health goods. We study the effect of time payments (micro-loans or micro-savings) on willingness-to-pay (WTP) for a water filter among households in the slums of Dhaka, Bangladesh. We find that time payments significantly increase WTP: compared to a lump-sum up-front purchase, median WTP increases 83% with a six-month loan and 115% with a 12-month loan. We find that households are quite patient with respect to consumption of health inputs. We find evidence for the presence of credit and savings constraints.

Gender, Behavioral Assessment of Negative Reinforcement Driven Risk Taking Propensity, and Cigarette Smoking

Cigarette smoking remains the leading preventable cause of death and disability in the United States and most often is initiated during adolescence. An emerging body of research suggests that a negative reinforcement model may explain factors that contribute to tobacco use during adolescence and that negative reinforcement processes may contribute to tobacco use to a greater extent among female adolescents than among male adolescents. However, the extant literature both on the relationship between negative reinforcement processes and adolescent tobacco use as well as on the relationship between gender, negative reinforcement processes, and adolescent tobacco use is limited by the sole reliance on self-report measures of negative reinforcement processes that may contribute to cigarette smoking. The current study aimed to further disentangle the relationships between negative reinforcement based risk taking, gender and tobacco use during older adolescence by utilizing a behavioral analogue measure of negative reinforcement based risk taking, the Maryland Resource for the Behavioral Utilization of the Reinforcement of Negative Stimuli (MRBURNS). Specifically, we examined the relationship between pumps on the MRBURNS, an indicator of risk taking, and smoking status as well as the interaction between MRBURNS pumps and gender for predicting smoking status. Participants included 103 older adolescents (n=51 smokers, 50.5% female, Age (M(SD) = 19.41(1.06)) who all attended one experimental session during which they completed the MRBURNS as well as self-report measures of tobacco use, nicotine dependence, alcohol use, depression, and anxiety. We utilized binary logistic regressions to examine the relationship between MRBURNS pumps and smoking status as well as the interactive effect of MRBURNS pumps and gender for predicting smoking status. Controlling for relevant covariates, pumps on the MRBURNS did not significantly predict smoking status and the interaction between pumps on the MRBURNS and gender also did not significantly predict smoking status. These findings highlight the importance of future research examining various task modifications to the MRBURNS as well as the need for replications of this study with larger, more diverse samples.