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Social and Behavioral Sciences Commons™
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Articles 1 - 30 of 40
Full-Text Articles in Social and Behavioral Sciences
Baseball Decision-Making: Optimizing At-Bat Simulations, Varun Gopal, Krithika Kondakindi, Nibhrat Lohia, Morgan Williams
Baseball Decision-Making: Optimizing At-Bat Simulations, Varun Gopal, Krithika Kondakindi, Nibhrat Lohia, Morgan Williams
SMU Data Science Review
Pitch selection in baseball plays a crucial role, involving pitchers, catchers, and batters working together. This practice, dating back to early baseball, has seen teams try various methods to gain an advantage. This research aims to use reinforcement learning and pitch-by-pitch Statcast data to improve batting strategies. It also builds on previous statistical work (sabermetrics) to make better choices in pitch selection and plate discipline. The dataset used, including over 700,000 pitches for each full season and 200,000 pitches for the COVID-shortened 2020 season, encompasses a wealth of crucial metrics including pitch release point, velocity, and launch angle. This study …
Thriving In College: International, First-Generation, And Transfer Students, Hannah Webb, Nikita Kulkarni, Dustin Grabsch
Thriving In College: International, First-Generation, And Transfer Students, Hannah Webb, Nikita Kulkarni, Dustin Grabsch
SMU Journal of Undergraduate Research
Underrepresented-student groups experience unique challenges throughout their college experience, the impacts of which can be assessed by measuring students’ levels of thriving. The purpose of this study was to understand the thriving of underrepresented college students—first-generation, international, and transfer students, specifically. To understand this, we sought to measure students’ thriving levels and determine the experiences contributing to or detracting from their perception of thriving. This study utilized a sequential exploratory design using the established 72-item thriving quotient survey to measure students’ overall thriving levels. In addition, the study utilized a qualitative content analysis on an open-ended question asking participants to …
Identifying Barriers To Mental Health Services Utilization For Black Youth In The United States: A Qualitative Study, Emily Stein, Matthew Hutnyan, Neely Myers
Identifying Barriers To Mental Health Services Utilization For Black Youth In The United States: A Qualitative Study, Emily Stein, Matthew Hutnyan, Neely Myers
SMU Journal of Undergraduate Research
Mental health in Black communities and racial/ethnic disparities in mental health service utilization remain growing concerns. Evidence suggests that psychotic disorders may be more prevalent among Black individuals than white individuals and the Black community faces barriers to care that can negatively influence outcomes. To better understand these barriers, we interviewed mental healthcare providers (n = 11) and Black young adults with first-person experience of psychosis (n = 13) about the experiences of minority young adults with mental health treatment. We analyzed interview transcripts and, consistent with constructivist grounded theory methods, identified iterative patterns across individuals about barriers to care. …
Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler
Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler
SMU Data Science Review
Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …
Using Geographic Information To Explore Player-Specific Movement And Its Effects On Play Success In The Nfl, Hayley Horn, Eric Laigaie, Alexander Lopez, Shravan Reddy
Using Geographic Information To Explore Player-Specific Movement And Its Effects On Play Success In The Nfl, Hayley Horn, Eric Laigaie, Alexander Lopez, Shravan Reddy
SMU Data Science Review
American Football is a billion-dollar industry in the United States. The analytical aspect of the sport is an ever-growing domain, with open-source competitions like the NFL Big Data Bowl accelerating this growth. With the amount of player movement during each play, tracking data can prove valuable in many areas of football analytics. While concussion detection, catch recognition, and completion percentage prediction are all existing use cases for this data, player-specific movement attributes, such as speed and agility, may be helpful in predicting play success. This research calculates player-specific speed and agility attributes from tracking data and supplements them with descriptive …
Bridging The Chasm Between Fundamental, Momentum, And Quantitative Investing, Allen Hoskins, Jeff Reed, Robert Slater
Bridging The Chasm Between Fundamental, Momentum, And Quantitative Investing, Allen Hoskins, Jeff Reed, Robert Slater
SMU Data Science Review
A chasm exists between the active public equity investment management industry's fundamental, momentum, and quantitative styles. In this study, the researchers explore ways to bridge this gap by leveraging domain knowledge, fundamental analysis, momentum, crowdsourcing, and data science methods. This research also seeks to test the developed tools and strategies during the volatile time period of 2020 and 2021.
Comparison Of Sampling Methods For Predicting Wine Quality Based On Physicochemical Properties, Robert Burigo, Scott Frazier, Eli Kravez, Nibhrat Lohia
Comparison Of Sampling Methods For Predicting Wine Quality Based On Physicochemical Properties, Robert Burigo, Scott Frazier, Eli Kravez, Nibhrat Lohia
SMU Data Science Review
Using the physicochemical properties of wine to predict quality has been done in numerous studies. Given the nature of these properties, the data is inherently skewed. Previous works have focused on handful of sampling techniques to balance the data. This research compares multiple sampling techniques in predicting the target with limited data. For this purpose, an ensemble model is used to evaluate the different techniques. There was no evidence found in this research to conclude that there are specific oversampling methods that improve random forest classifier for a multi-class problem.
Content-Based Unsupervised Fake News Detection On Ukraine-Russia War, Yucheol Shin, Yvan Sojdehei, Limin Zheng, Brad Blanchard
Content-Based Unsupervised Fake News Detection On Ukraine-Russia War, Yucheol Shin, Yvan Sojdehei, Limin Zheng, Brad Blanchard
SMU Data Science Review
The Ukrainian-Russian war has garnered significant attention worldwide, with fake news obstructing the formation of public opinion and disseminating false information. This scholarly paper explores the use of unsupervised learning methods and the Bidirectional Encoder Representations from Transformers (BERT) to detect fake news in news articles from various sources. BERT topic modeling is applied to cluster news articles by their respective topics, followed by summarization to measure the similarity scores. The hypothesis posits that topics with larger variances are more likely to contain fake news. The proposed method was evaluated using a dataset of approximately 1000 labeled news articles related …
Examining Bias In Jury Selection For Criminal Trials In Dallas County, Megan Ball, Brandon Birmingham, Matt Farrow, Katherine Mitchell, Bivin Sadler, Lynne Stokes
Examining Bias In Jury Selection For Criminal Trials In Dallas County, Megan Ball, Brandon Birmingham, Matt Farrow, Katherine Mitchell, Bivin Sadler, Lynne Stokes
SMU Data Science Review
One of the hallmarks of the American judicial system is the concept of trial by jury, and for said trial to consist of an impartial jury of your peers. Several landmark legal cases in the history of the United States have challenged this notion of equal representation by jury—most notably Batson v. Kentucky, 476 U.S. 79 (1986). Most of the previous research, focus, and legal precedence has centered around peremptory challenges and attempting to prove if bias was suspected in excluding certain jurors from serving. Few studies, however, focus on examining challenges for cause based on self-reported biases from the …
Application Of Probabilistic Ranking Systems On Women’S Junior Division Beach Volleyball, Cameron Stewart, Michael Mazel, Bivin Sadler
Application Of Probabilistic Ranking Systems On Women’S Junior Division Beach Volleyball, Cameron Stewart, Michael Mazel, Bivin Sadler
SMU Data Science Review
Women’s beach volleyball is one of the fastest growing collegiate sports today. The increase in popularity has come with an increase in valuable scholarship opportunities across the country. With thousands of athletes to sort through, college scouts depend on websites that aggregate tournament results and rank players nationally. This project partnered with the company Volleyball Life, who is the current market leader in the ranking space of junior beach volleyball players. Utilizing the tournament information provided by Volleyball Life, this study explored replacements to the current ranking systems, which are designed to aggregate player points from recent tournament placements. Three …
Adjusting Community Survey Data Benchmarks For External Factors, Allen Miller, Nicole M. Norelli, Robert Slater, Mingyang N. Yu
Adjusting Community Survey Data Benchmarks For External Factors, Allen Miller, Nicole M. Norelli, Robert Slater, Mingyang N. Yu
SMU Data Science Review
Abstract. Using U.S. resident survey data from the National Community Survey in combination with public data from the U.S. Census and additional sources, a Voting Regressor Model was developed to establish fair benchmark values for city performance. These benchmarks were adjusted for characteristics the city cannot easily influence that contribute to confidence in local government, such as population size, demographics, and income. This adjustment allows for a more meaningful comparison and interpretation of survey results among individual cities. Methods explored for the benchmark adjustment included cluster analysis, anomaly detection, and a variety of regression techniques, including random forest, ridge, decision …
Corpus Linguistics Criticisms Of Heller Misuse Corpus Linguistics, Michael Showalter
Corpus Linguistics Criticisms Of Heller Misuse Corpus Linguistics, Michael Showalter
SMU Law Review Forum
A number of linguistics experts have asserted that new corpus-linguistics evidence undermines the U.S. Supreme Court’s conclusion in District of Columbia v. Heller that the Second Amendment phrase keep and bear arms means to possess and carry weapons. At the time of ratification, the term bear arms carried both an idiomatic sense meaning “to serve as a soldier” and a literal sense meaning “to carry weapons.” The Heller majority concluded that the Second Amendment uses the literal sense, partly because the idiomatic reading has the absurd implication of causing the Amendment to protect a right to serve as a soldier. …
Aspect-Based Sentiment Analysis Of Movie Reviews, Samuel Onalaja, Eric Romero, Bosang Yun
Aspect-Based Sentiment Analysis Of Movie Reviews, Samuel Onalaja, Eric Romero, Bosang Yun
SMU Data Science Review
This study investigates a comparison of classification models used to determine aspect based separated text sentiment and predict binary sentiments of movie reviews with genre and aspect specific driving factors. To gain a broader classification analysis, five machine and deep learning algorithms were compared: Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM), and Recurrent Neural Network Long-Short-Term Memory (RNN LSTM). The various movie aspects that are utilized to separate the sentences are determined through aggregating aspect words from lexicon-base, supervised and unsupervised learning. The driving factors are randomly assigned to various movie aspects and their impact tied to …
Urban Traffic Simulation: Network And Demand Representation Impacts On Congestion Metrics, Aaron Faltesek, Balasubramaniam Dakshinamoorthi, Sreeni Prabhala, Akbar Thobani, Anu Kuncheria, Jane Macfarlane
Urban Traffic Simulation: Network And Demand Representation Impacts On Congestion Metrics, Aaron Faltesek, Balasubramaniam Dakshinamoorthi, Sreeni Prabhala, Akbar Thobani, Anu Kuncheria, Jane Macfarlane
SMU Data Science Review
Traffic simulations are often used by city planners as a basis for predicting the impact of policies, plans, and operations. The complexities underpinning traffic simulations are often not described in detail yet can significantly impact the simulation outcome. Conflating underlying data for simulations is complex and hinders the interest in this type of exploration. This paper aims to elucidate critical features of traffic simulations that drive the generated metrics of the modeled urban environment. Specifically, this paper examines differences in two road graph networks for the metropolitan region of Houston, TX: a reduced network composed of 45,675 road links and …
Using Machine Learning Methods To Predict The Movement Trajectories Of The Louisiana Black Bear, Daniel Clark, David Shaw, Armando Vela, Shane Weinstock, John Santerre, Joseph D. Clark
Using Machine Learning Methods To Predict The Movement Trajectories Of The Louisiana Black Bear, Daniel Clark, David Shaw, Armando Vela, Shane Weinstock, John Santerre, Joseph D. Clark
SMU Data Science Review
In 1992, the Louisiana black bear (Ursus americanus luteolus) was placed on the U.S. Endangered Species List. This was due to bear populations in Louisiana being small and isolated enough where their populations couldn’t intersect with other populations to grow. Interchange of individuals between subpopulations of bears in Louisiana is critical to maintain genetic diversity and avoid inbreeding effects. Utilizing GPS (Global Positioning System) data gathered from 31 radio-collared bears from 2010 through 2012, this research will investigate how bears traverse the landscape, which has implications for gene exchange. This paper will leverage machine learning tools to improve upon existing …
Analysis Of Individual Player Performances And Their Effect On Winning In College Soccer, Angelo Bravo, Thomas Karba, Sean Mcwhirter, Billy Nayden
Analysis Of Individual Player Performances And Their Effect On Winning In College Soccer, Angelo Bravo, Thomas Karba, Sean Mcwhirter, Billy Nayden
SMU Data Science Review
This study describes the process of modernizing the approach of the Southern Methodist University (SMU) Men's Soccer coaching staff through the use of location and tracking data from their matches in the 2019 season. This study utilizes a variety of modeling and analysis techniques to explore and categorize the data and use it to evaluate the types of plays that are most often correlated with victories. This study's contribution to college soccer analytics includes the implementation of a model to determine individual players' performance, the production of team-level metrics, and visualizations to increase the efficiency of the coaching staff's efforts. …
The Data Market: A Proposal To Control Data About You, David Shaw, Daniel W. Engels
The Data Market: A Proposal To Control Data About You, David Shaw, Daniel W. Engels
SMU Data Science Review
The current legal and economic infrastructure facilitating data collection practices and data analysis has led to extreme over-collection of data and the overall loss of personal privacy. Data over-collection has led to a secondary market for consumer data that is invisible to the consumer and results in a person's data being distributed far beyond their knowledge or control. In this paper, we propose a Data Market framework and design for personal data management and privacy protection in which the individual controls and profits from the dissemination of their data. Our proposed Data Market uses a market-based approach utilizing blockchain distributed …
The Effects Of Group Music Therapy On Levels Of Anxiety, Depression, Well-Being, Functional Disability, And Distress In Adult Congolese Refugees, Elise Hawkes
SMU Journal of Undergraduate Research
Refugees have a variety of mental health needs due to their experiences, including trauma, anxiety, and depression. Psychotherapy, one of the main modalities for treatment, presents limitations including language barriers and negative stigmas. Music therapy might help to overcome these limitations due to its reliance upon music, rather than verbal language, as the therapeutic medium, and due to music’s ubiquitous cultural prevalence. Music therapy has been shown to have positive effects on sleep quality, well-being, trauma symptoms, social function, and mood. Music therapy training and research results have demonstrated ways to connect with clients through music and overcome cross-cultural barriers. …
The Latitudinarian Influence On Early English Liberalism, Amanda Oh
The Latitudinarian Influence On Early English Liberalism, Amanda Oh
SMU Journal of Undergraduate Research
This paper takes the unexpected position that early liberal thought developed in transformative events within the Anglican Church during the second half of the seventeenth century. The historical evolution of religion laid the foundation of English political and intellectual philosophy, as supported by works written by the branch of Anglican churchmen known as the Latitudinarians. I will argue that these ministers were foremost in advancing the argument for religious toleration because their religious writings held political consequence. Toleration was the principle value of liberalism in the late seventeenth century because the problem of Dissenters was so pertinent to English religious …
Comparing Intersubject Correlation (Isc) Between Autism Spectrum Disorder And Typically Developed Groups To Better Understand Biological Motion Processing, Elena Skaribas
SMU Journal of Undergraduate Research
In this study, we addressed significant neurological differences between autistic and typically developed individuals, specifically when processing biological motion, using Intersubject correlation (ISC) analysis methods. ISC is a tool used to analyze functional magnetic resonance imaging (fMRI) data acquired under naturalistic stimuli. Using ISC, it is possible to pinpoint common brain responses within a group of individuals as they react to a specific stimulus. ISC is also used to highlight the different brain responses two different groups might have while experiencing the same stimulus. In this experiment, we used two subject groups, one group of autism spectrum disorder (ASD) individuals …
Personalized Detection Of Anxiety Provoking News Events Using Semantic Network Analysis, Jacquelyn Cheun Phd, Luay Dajani, Quentin B. Thomas
Personalized Detection Of Anxiety Provoking News Events Using Semantic Network Analysis, Jacquelyn Cheun Phd, Luay Dajani, Quentin B. Thomas
SMU Data Science Review
In the age of hyper-connectivity, 24/7 news cycles, and instant news alerts via social media, mental health researchers don't have a way to automatically detect news content which is associated with triggering anxiety or depression in mental health patients. Using the Associated Press news wire, a semantic network was built with 1,056 news articles containing over 500,000 connections across multiple topics to provide a personalized algorithm which detects problematic news content for a given reader. We make use of Semantic Network Analysis to surface the relationship between news article text and anxiety in readers who struggle with mental health disorders. …
A Data Science Approach To Defining A Data Scientist, Andy Ho, An Nguyen, Jodi L. Pafford, Robert Slater
A Data Science Approach To Defining A Data Scientist, Andy Ho, An Nguyen, Jodi L. Pafford, Robert Slater
SMU Data Science Review
In this paper, we present a common definition and list of skills for a Data Scientist using online job postings. The overlap and ambiguity of various roles such as data scientist, data engineer, data analyst, software engineer, database administrator, and statistician motivate the problem. To arrive at a single Data Scientist definition, we collect over 8,000 job postings from Indeed.com for the six job titles. Each corpus contains text on job qualifications, skills, responsibilities, educational preferences, and requirements. Our data science methodology and analysis rendered the single definition of a data scientist: A data scientist codes, collaborates, and communicates – …
Leveraging Natural Language Processing Applications And Microblogging Platform For Increased Transparency In Crisis Areas, Ernesto Carrera-Ruvalcaba, Johnson Ekedum, Austin Hancock, Ben Brock
Leveraging Natural Language Processing Applications And Microblogging Platform For Increased Transparency In Crisis Areas, Ernesto Carrera-Ruvalcaba, Johnson Ekedum, Austin Hancock, Ben Brock
SMU Data Science Review
Through microblogging applications, such as Twitter, people actively document their lives even in times of natural disasters such as hurricanes and earthquakes. While first responders and crisis-teams are able to help people who call 911, or arrive at a designated shelter, there are vast amounts of information being exchanged online via Twitter that provide real-time, location-based alerts that are going unnoticed. To effectively use this information, the Tweets must be verified for authenticity and categorized to ensure that the proper authorities can be alerted. In this paper, we create a Crisis Message Corpus from geotagged Tweets occurring during 7 hurricanes …
Dallas Refugee Engagement Project, Anna Landreneau, Kovan Barzani, Uroob Haris, Lawrence Jiang, Michael Park, Thomas Schmedding
Dallas Refugee Engagement Project, Anna Landreneau, Kovan Barzani, Uroob Haris, Lawrence Jiang, Michael Park, Thomas Schmedding
SMU Journal of Undergraduate Research
The full capabilities of well-structured project management are rarely realized outside of the scope of the respective profession. The tools and skills in which project managers specialize are furthermore often considered in high-level business contexts, but are far less remembered as crucial components to many other endeavors. This project portfolio serves as an insight into the structure and process of managing a short-term social awareness project and an exploration and application of various project management tools. It also provides a review of the success of implementing sound project management toward humanitarian work on a community level. Public Equity, the team …
The Effect Of The 2016 Presidential Election On Sikh-Americans’ Perceptions Of Safety In Texas, Jasleen Dhillon
The Effect Of The 2016 Presidential Election On Sikh-Americans’ Perceptions Of Safety In Texas, Jasleen Dhillon
SMU Journal of Undergraduate Research
Since the 9/11 terrorist attacks on the World Trade Center, members of the Sikh-American community have been the subjects of random hate crimes in the United States because of their distinct identity, namely the turban. During and after the 2016 presidential election, many minority groups, including Sikh-Americans, were concerned over the rhetoric the then-candidate Donald Trump had been using. The focus of this research project was to study if the rhetoric used during the presidential campaign had any effect on how Sikh-Americans perceived their safety in a politically conservative state like Texas. The methods used to collect data were both …
Initiatives To Effectively Help Reduce Traffic Congestion In The Tri-Valley, Paola Selene Leon Castaneda, Christian Joseph Catalano
Initiatives To Effectively Help Reduce Traffic Congestion In The Tri-Valley, Paola Selene Leon Castaneda, Christian Joseph Catalano
SMU Data Science Review
In this paper, we present a comprehensive analysis of the current transit systems in the Tri-Valley of the Eastern Region of the San Francisco Bay Area. Using the most recent data available from various sources and significant research we provide a close look into ridership trends, public surveys and transit reports. System maps, connections, routes and schedules are analyzed from all the mass transit systems available in the Tri-Valley region. Transit system infrastructure, resources and limitations are assessed and presented. Different performance metrics are also evaluated and compared against mass transit systems available in other parts of the San Francisco …
Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels
Finding Truth In Fake News: Reverse Plagiarism And Other Models Of Classification, Matthew Przybyla, David Tran, Amber Whelpley, Daniel W. Engels
SMU Data Science Review
As the digital age creates new ways of spreading news, fake stories are propagated to widen audiences. A majority of people obtain both fake and truthful news without knowing which is which. There is not currently a reliable and efficient method to identify “fake news”. Several ways of detecting fake news have been produced, but the various algorithms have low accuracy of detection and the definition of what makes a news item ‘fake’ remains unclear. In this paper, we propose a new method of detecting on of fake news through comparison to other news items on the same topic, as …
Political Profiling Using Feature Engineering And Nlp, Chiranjeevi Mallavarapu, Ramya Mandava, Sabitri Kc, Ginger M. Holt
Political Profiling Using Feature Engineering And Nlp, Chiranjeevi Mallavarapu, Ramya Mandava, Sabitri Kc, Ginger M. Holt
SMU Data Science Review
Public surveys are predominantly used when forecasting election outcomes. While the approach has had significant successes, the surveys have had their failures as well, especially when it comes to accuracy and reliability. As a result, it becomes challenging for political parties to spend their campaign budgets in a manner that facilitates the growth of a favorable and verifiable public opinion. Consequently, it is critical that a more accurate methodology to predict election outcome is developed. In this paper, we present an evaluation of the impact of utilizing dynamic public data on predicting the outcome of elections. Our model yielded a …
Framework For Evaluation Of Flash Flood Models In Wildfire-Prone Areas, Brian Cunningham, David Benepe, Bryan Cikatz, Evangelos Giakoumakis
Framework For Evaluation Of Flash Flood Models In Wildfire-Prone Areas, Brian Cunningham, David Benepe, Bryan Cikatz, Evangelos Giakoumakis
SMU Data Science Review
Abstract. In this paper, we present an innovative framework for evaluating the increased risk of flash flooding in areas that have been subjected to wildfires. Wildfires cause large-scale damage to an area’s soil and vegetation thus increasing both the likelihood and severity of flash flooding. Utilizing remote sensing to analyze aerial imagery of areas that have been affected by wildfires, we can investigate how much a landscape has changed and how that may adversely affect downstream areas in the event of a flash flooding event. There are currently no established frameworks from which downstream local officials can quickly assess the …
Improvements To Consumption Prediction: Machine Learning Methods And Novel Features, Ian Kinskey, Glenn Oswald, Charles Mccann, Travis Finch, Anthony Tanaydin
Improvements To Consumption Prediction: Machine Learning Methods And Novel Features, Ian Kinskey, Glenn Oswald, Charles Mccann, Travis Finch, Anthony Tanaydin
SMU Data Science Review
Current models for predicting personal consumption expenditures (PCE) employ statistical techniques and rely upon traditional economic features. We compare vector autoregression and random forest regression models using traditional economic features as inputs to predict PCE. Additionally, we develop novel features derived from the earnings call transcripts of publicly traded U.S. companies using natural language processing (NLP) techniques. These new features reduce the mean square error (MSE) of the vector autoregression model by 7% and the random forest model by 23%. We find the random forest models outperformed the vector autoregression models, with a MSE reduction of 68%. We conclude the …