Social and Behavioral Sciences Commons^™

Stand-Up Comedy Visualized, Berna Yenidogan

Dissertations, Theses, and Capstone Projects

Stand-up comedy has become an increasingly popular form of comedy in the recent years and comedians reach audiences beyond the halls they are performing through streaming services, podcasts and social media. While comedic performances are typically judged by how 'funny' they are, which could be proxied by the frequency and intensity of laughs through the performance, comedians also explore untapped social issues and provoke conversation, especially in this age where interaction with artists goes beyond their act. It is easy to see commonalities in the topics addressed in comedians’ work such as relationships, race and politics.This project provides an interactive …

Essays On Machine Learning Methods In Economics, Mani Bayani

Dissertations, Theses, and Capstone Projects

This dissertation consists of three chapters on machine learning modeling in economics. Chapter 1 - Robust PCA Synthetic Control: In this chapter, I propose an algorithm for comparative studies called robust PCA synthetic control. My algorithm builds on the synthetic control model of Abadie et al., 2015 and the robust synthetic control model of Amjad et al., 2018. I apply all three methods (robust PCA synthetic control, synthetic control, and robust synthetic control) to answer the hypothetical question, what would have been the per capita GDP of West Germany if it had not reunified with East Germany in 1990? I …

Happiness And Policy Implications: A Sociological View, Sarah M. Kahl

Dissertations, Theses, and Capstone Projects

The World Happiness Report is released every year, ranking each country by who is “happier” and explaining the variables and data they have used. This project attempts to build from that base and create a machine learning algorithm that can predict if a country will be in a “happy” or “could be happier” category. Findings show that taking a broader scope of variables can better help predict happiness. Policy implications are discussed in using both big data and considering social indicators to make better and lasting policies.

Three Essays On Natural Rates, Huseyin U. Demir

Dissertations, Theses, and Capstone Projects

Chapter 1. Non-accelerating inflation rate of unemployment and Non-accelerating inflation rate of output We followed Ball and Mankiw (2002) to estimate the natural rates of output and unemployment. The primary purposes of this paper are to provide more accurate estimates of a varying non-accelerating inflation rate of unemployment (NAIRU) than currently exist and to nd a new measure for the nonaccelerating inflation rate of output so we can estimate the output gap more accurately. Our contributions are adding time-varying coefficients estimated with a break test and finding more accurate measurements for the natural rate of unemployment. We also estimated the …

Applications Of Machine Learning And Deep Learning In Macroeconomic And Financial Forecasting, Andi Cupallari

Dissertations, Theses, and Capstone Projects

This dissertation consists of three chapters.

In the first chapter I propose a novel approach to forecast risk premia selecting relevant predictors among hundreds of correlated stock characteristics. I adapt a recently developed method from the deep learning literature, Deep Neural Networks with Group Lasso Regular- ization. This method achieves high out of sample R2, and at the same time yields a sparse representation of the characteristics space that allows for interpretability of the otherwise black box deep learning model. For each period, the model chooses a subset of characteris- tics to be relevant for the risk premia forecast. Our …

Phonologically-Informed Speech Coding For Automatic Speech Recognition-Based Foreign Language Pronunciation Training, Anthony J. Vicario

Dissertations, Theses, and Capstone Projects

Automatic speech recognition (ASR) and computer-assisted pronunciation training (CAPT) systems used in foreign-language educational contexts are often not developed with the specific task of second-language acquisition in mind. Systems that are built for this task are often excessively targeted to one native language (L1) or a single phonemic contrast and are therefore burdensome to train. Current algorithms have been shown to provide erroneous feedback to learners and show inconsistencies between human and computer perception. These discrepancies have thus far hindered more extensive application of ASR in educational systems.

This thesis reviews the computational models of the human perception of American …

Essays On Applied Machine Learning For Implied Volatility Interpolation And Artificial Counterfactuals, Pablo A. Crespo

Dissertations, Theses, and Capstone Projects

This dissertation consists of two chapters.

Chapter 1: Volatility estimates under the risk neutral density have become a much revisited topic of interest in recent years. The density proves itself a powerful tool for sentiment analysis, since its moments provide insights about expectations in price trends. A standard procedure for its extraction utilizes artificial volatility predictions to form a dense enough grid for approximating a complete probability distribution. This paper proposes two common machine learning technique variations to produce implied volatility predictions when data is very scarce. First, a model using regularization through a variation of a generalized LASSO path …

Multimodal Depression Detection: An Investigation Of Features And Fusion Techniques For Automated Systems, Michelle Renee Morales

Dissertations, Theses, and Capstone Projects

Depression is a serious illness that affects a large portion of the world’s population. Given the large effect it has on society, it is evident that depression is a serious health issue. This thesis evaluates, at length, how technology may aid in assessing depression. We present an in-depth investigation of features and fusion techniques for depression detection systems. We also present OpenMM: a novel tool for multimodal feature extraction. Lastly, we present novel techniques for multimodal fusion. The contributions of this work add considerably to our knowledge of depression detection systems and have the potential to improve future systems by …