Data Science Commons^™

Heating Fire Incidents In New York City, Merissa K. Lissade

Dissertations, Theses, and Capstone Projects

If you have ever had the Citizen app downloaded on your smart phone, then you know how many alerts you receive in a day living in New York City (NYC). Citizen is a mobile app that sends real-time safety alerts based on the location of its user. In my experience having the app, I have seen many notifications of fires caused by heaters during the winter. On the morning of January 9^th, 2022, I received a notification of an accidental blaze that took the lives of 17 people from the choking smoke of a 19-story residential building in …

Why, New York City? Gauging The Quality Of Life Through The Thoughts Of Tweeters, Sheryl Williams

Dissertations, Theses, and Capstone Projects

As a resource for social data, Twitter’s platform has been used to measure the quality of life through sentiment analysis. This capstone project explores another methodological technique—querying Twitter data around specific keyword terms to determine dominant topics, word patterns, and sentiment leanings in a geographical area. Focusing on New York City and Los Angeles for comparative analysis, the keyword term “why” will be used to build a Python analysis around topic modeling and sentiment analysis. Using this approach, the analysis reveals social and cultural differences, the overall sentiment of tweets, and subjects of interest to tweeters.

GitHub Repository for all …

Exploring The Effectiveness Of Multiple-Exemplar Training For Visual Analysis Of Ab-Design Graphs, Verena S. Bethke

Dissertations, Theses, and Capstone Projects

In behavior analysis, data are usually analyzed using visual analysis of the graphed data. There are a wide range of methods used to visually analyze data, from a basic ‘textbook’ style approach to the use of visual aids, decision-rubrics, and computer-based approaches. In the literature, there have been some comparisons of the efficacy of different approaches. Visual analysis as a behavior can be taught using a variety of methods, independent of how the skill itself is to be performed. Teaching methods include lecture, online instruction, and equivalence-based instruction. There is not much research on the teaching of visual analysis specifically, …

Representation Learning For Chemical Activity Predictions, Mohamed S. Ayed

Dissertations, Theses, and Capstone Projects

Computational prediction of a phenotypic response upon the chemical perturbation on a biological system plays an important role in drug discovery and many other applications. Chemical fingerprints derived from chemical structures are a widely used feature to build machine learning models. However, the fingerprints ignore the biological context, thus, they suffer from several problems such as the activity cliff and curse of dimensionality. Fundamentally, the chemical modulation of biological activities is a multi-scale process. It is the genome-wide chemical-target interactions that modulate chemical phenotypic responses. Thus, the genome-scale chemical-target interaction profile will more directly correlate with in vitro and in …

Blockchain: Key Principles, Nadezda Chikurova

Dissertations, Theses, and Capstone Projects

“Blockchain: Key Principles” is an interactive visual project that explains the importance of data privacy and security, decentralized computing, and open-source software in the modern digital world through the history of the underlying principles of blockchain technology. Some of these key concepts have their roots in the time before the Information Age. By explaining the history of these principles, I want to present the fact that over the past centuries, humanity has been fighting for their privacy, security, and the ability to efficiently express themselves one way or another. Blockchain technology, which was introduced to the public in 2008 through …

Air Pollution, Climate Change, And Our Health, Kathia Vargas Feliz

Dissertations, Theses, and Capstone Projects

Climate change is a subject that is creating a lot of controversies nowadays. From newspapers to researchers, there are big efforts going on trying to bring awareness about the effects of air pollution and climate change over time. It is recommended that governments all over the world, and people from all communities act by taking care of the environment because the situation might turn out to be irremediable. There is a quote by Leonardo Dicaprio stating, “Climate change is real. It is happening right now; it is the most urgent threat facing our entire species and we need to …

Liquidity Commonality With Factor Models, Ernesto Garcia Iii

Dissertations, Theses, and Capstone Projects

Market microstructure research has recently devoted attention to a phenomenon called commonality in liquidity. In this dissertation, I will analyze commonality in liquidity using a novel factor model approach and a generalized definition of commonality in liquidity. This analysis will show that commonality in liquidity is rarely a marketwide phenomenon and is mostly restricted to stocks with a large market capitalization. Additionally, commonality in liquidity is a very recent phenomenon whose appearance coincides with a rise in passive investing after the Dotcom Bubble burst and, more so, after the 2008 Financial Crisis. I will present evidence that suggests commonality in …

Piecewise Linear Manifold Clustering, Artyom Diky

Dissertations, Theses, and Capstone Projects

This work studies the application of topological analysis to non-linear manifold clustering. A novel method, that exploits the data clustering structure, allows to generate a topological representation of the point dataset. An analysis of topological construction under different simulated conditions is performed to explore the capabilities and limitations of the method, and demonstrated statistically significant improvements in performance. Furthermore, we introduce a new information-theoretical validation measure for clustering, that exploits geometrical properties of clusters to estimate clustering compressibility, for evaluation of the clustering goodness-of-fit without any prior information about true class assignments. We show how the new validation measure, when …

Detecting Stance On Covid-19 Vaccine In A Polarized Media, Rodica Ceslov

Dissertations, Theses, and Capstone Projects

The growing polarization in the United States has been widely reported. Media coverage plays an important role in shaping public opinion and influences public debates on complex and unfamiliar topics. There are some benefits to individuals and society from political polarization and conflict between opposing viewpoints. However, recent research has primarily highlighted the negative consequences of polarization which reached an all-time high. One such topic is the Covid-19 vaccine which was developed in record time, and the public learned about its safety and possible risks through the media coverage.

In this capstone, we examine U.S. news media coverage on the …

Making Space For Unquantifiable Data: Hand-Drawn Data Visualization, Eva Sibinga

Dissertations, Theses, and Capstone Projects

This project makes space for personal “data” around labor and care, prompting users to consider the concrete and abstract (quantifiable and unquantifiable) forms labor and care take in their lives. The interactive, subjective data visualization uses hand-drawn visual elements to foreground that data about care and human interaction will always be ambiguous and complex, that they may never be satisfactorily or universally quantified, and that they will always be out of reach of perfect categorization.

The project provides an alternative to prescriptive truth-telling with data. Instead of using a dataset to provide data-driven answers and insights to users, the interactive …

Learn Biologically Meaningful Representation With Transfer Learning, Di He

Dissertations, Theses, and Capstone Projects

Machine learning has made significant contributions to bioinformatics and computational biol­ogy. In particular, supervised learning approaches have been widely used in solving problems such as bio­marker identification, drug response prediction, and so on. However, because of the limited availability of comprehensively labeled and clean data, constructing predictive models in super­ vised settings is not always desirable or possible, especially when using data­hunger, red­hot learning paradigms such as deep learning methods. Hence, there are urgent needs to develop new approaches that could leverage more readily available unlabeled data in driving successful machine learning ap­ plications in this area.

In my dissertation, …

A New Feature Selection Method Based On Class Association Rule, Sami A. Al-Dhaheri

Dissertations, Theses, and Capstone Projects

Feature selection is a key process for supervised learning algorithms. It involves discarding irrelevant attributes from the training dataset from which the models are derived. One of the vital feature selection approaches is Filtering, which often uses mathematical models to compute the relevance for each feature in the training dataset and then sorts the features into descending order based on their computed scores. However, most Filtering methods face several challenges including, but not limited to, merely considering feature-class correlation when defining a feature’s relevance; additionally, not recommending which subset of features to retain. Leaving this decision to the end-user may …

Machine Learning Applications For Drug Repurposing, Hansaim Lim

Dissertations, Theses, and Capstone Projects

The cost of bringing a drug to market is astounding and the failure rate is intimidating. Drug discovery has been of limited success under the conventional reductionist model of one-drug-one-gene-one-disease paradigm, where a single disease-associated gene is identified and a molecular binder to the specific target is subsequently designed. Under the simplistic paradigm of drug discovery, a drug molecule is assumed to interact only with the intended on-target. However, small molecular drugs often interact with multiple targets, and those off-target interactions are not considered under the conventional paradigm. As a result, drug-induced side effects and adverse reactions are often neglected …

A Data Exploration Of Jeopardy! From 1984 To The Present, Brian S. Hamilton

Dissertations, Theses, and Capstone Projects

The gameshow Jeopardy! has been around in its current iteration—hosted by Alex Trebek—since 1984. During this time, it has accumulated data on clues, contestants, and possible strategies on how to win. Using a crowd-sourced archive called J! Archive, this project seeks to find trends in the topics that the game covers and take a deeper look into the performance of its contestants. It employs topic modeling, a text-analysis method, to organize the hundreds of thousands of archived clues and statistical analysis to rate the performance of contestants by gender. Using web-based visualization tools, the data is shown in an …