Data Science Commons^™

Digital Technology Enables Construction Of National Governance Modernization, Yue Hao, Kaihua Chen, Jin Kang, Xiaoguang Yang, Chao Zhang, Xiaolong Zheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

As digital technologies continue to be integrated into the whole process of economic and social development, promoting the modernization of digital technology-enabled national governance systems and capabilities has become an important way to seize the strategic initiative in the future world competitive landscape, and has attracted the attention of countries around the world. The rapid development of digital technologies such as big data collection, storage, processing, and analysis is constantly optimizing the organizational system structure of national governance, upgrading and perfecting the quality and methods of national governance personnel, and accelerating the process of making national governance efficient, scientific, intelligent …

Deepening Digital Technologies To Enable Modernization Of China’S Governance Of Health, Tara Qia Sun, Xia Feng, Yuntao Long, Zongben Xu

Bulletin of Chinese Academy of Sciences (Chinese Version)

One significant goal of science and technology innovation is to set our sights on the health and safety of the people. The rapid development of digital technologies provides multiple potentials and path to achieve the modernization of China's health governance. the role of digital technologies on enabling multiple stakeholders (i.e., hospitals, doctors, government, and social groups) to improve the supply capacity, the inclusiveness, fairness, friendliness, and convenience of health service. Second, we explore the four key issues of using digital technologies to enable the governance of health construction of digital health infrastructures, the factors affecting the adoption of digital technologies, …

Digital Technology Enables Modernization Of National Statistics, Zongben Xu, Yanyun Zhao, Liping Zhu, Guang Chen, Hongyun Zhang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The modernization of national statistics is part of the modernization of national governance. Digital technology has provided power for the transformation of statistical production mode, the improvement of statistical productivity, and the reconstruction of statistical production relations. Digital technology has become an important prerequisite for the promotion of statistical modernization reform. This study summarizes the international experience of digital technology enabling government statistics, the top-level design of national statistical legal system, and the importance of digital technology in promoting the modernization of statistics. This study also analyzes the main challenges existing in the current national statistics and data work. Finally, …

Big Data Technology Enabling Legal Supervision, Qingjie Liu, Shuo Liu, Yirong Wu, Yueqiang Weng, Yihao Wen, Ming Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Legal supervision plays an important role in the national governance system and capacity. In the era of digital revolution, the rapid development of digital procuratorial work with big data legal supervision as the core promotes to reshape the legal supervision and governance system. In this study, the inherent need of legal supervision for active prosecution in the new era, and the innovative role of new public interest litigation in comprehensive social governance, are firstly analyzed. Then, the core meaning and reshaping role of big-data-enabling-legalsupervision and supervision-promoting-national-governance of digital prosecution are discussed. After summarizing the practical experiences and challenges of big …

Strengthen Fundamental Role Of Data Element Governance In National Governance Modernization, Kaihua Chen, Zhuo Feng, Rui Guo, Yue Hao, Jin Kang, Xiaoguang Yang, Chao Zhang, Binbin Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Data element governance is a key factor to promote the modernization of national governance in the digital era. By strengthening the deep integration of data factors and national governance, a new model of data-driven national governance can be formed, and the national governance can be made more scientific, refined, intelligent, and efficient. The US and European countries have continuously strengthened the top-level system design, technological innovation application, collaborative governance mechanism, and global governance cooperation of data element governance, which has effectively improved the level of data element governance and provided experience for China. Nevertheless, due to the virtuality of data …

Strategic Perspective Of Leveraging New Generation Information Technology To Enable Modernization Of Emergency Management, Haibo Zhang, Xinyu Dai, Depei Qian, Jian Lyu

Bulletin of Chinese Academy of Sciences (Chinese Version)

The application and development of the new generation information technology is a vital support to realize the modernization of emergency management. At present, the new generation information technology such as big data and artificial intelligence has been widely used in natural disasters, safe production, and other fields. It has improved the monitoring and early warning, regulation and law enforcement, command and decision support, rescue, and social mobilization capabilities of governments, promoted the level of intrinsic safety of enterprises, provided important support for the precise prevention and control of the COVID-19, and increased the efficiency of China’s emergency management and sense …

Utilizing Remote Sensing Technology To Relocate Lubra Village And Visualize Flood Damages, Ronan Wallace

Mathematics, Statistics, and Computer Science Honors Projects

As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community and habitat-conscious solutions. In Himalayan Mustang, Nepal, indigenous Lubra village faces threats of increasing flash flooding. After every flood, residual concrete-like sediment hardens across the riverbed, causing the riverbed elevation to rise. As elevation increases, sediment encroaches on Lubra’s agricultural fields and homes, magnifying flood vulnerability. In the last monsoon season alone, the village witnessed floods swallowing several fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as eight centuries …

Spatial Validation Of Agent-Based Models, Kristoffer Wikstrom, Hal T. Nelson

Public Administration Faculty Publications and Presentations

This paper adapts an existing techno–social agent-based model (ABM) in order to develop a new framework for spatially validating ABMs. The ABM simulates citizen opposition to locally unwanted land uses, using historical data from an energy infrastructure siting process in Southern California. Spatial theory, as well as the model’s design, suggest that adequate validation requires multiple tests rather than relying solely on a single test-statistic. A pattern-oriented modeling approach was employed that first mapped real and simulated citizen comments across the US Census tract. The suite of spatial tests included Global Moran’s I, complemented with bivariate correlations, as well as …

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …

Transfer Of Personality Through Text Style, Michael O'Mahony, Robert Ross

Other resources

The style of generated text is how something is said rather than what is said. We hypothesize that changing the style of generated text can change the perceived personality of the text generation agent. Dialogue systems that aim to imitate a human agent can appear to have a consistent personality through a consistent, controllable style of conversation. Some recent work on the style of generated text [1] performs impressively in the small number of domains selected for their experiments using transformer and LSTM-based models. Lin et al. [1] used weak supervised learning as their data set lacks parallel data. The …

Safe Sharing For Sensitive Data, Kristi Thompson

Western Libraries Presentations

This workshop focused on the question of when and how human subjects' data can be safely shared. It introduced the basics of data anonymization and discussed how to tell if a dataset has been de-identified. Case studies of successful anonymization and some spectacular failures were shared

Causal Inference In Psychology And Neuroscience: From Association To Causation, Dehua Liang

Computational and Data Sciences (PhD) Dissertations

In psychology and neuroscience, inferring causality in non-experimental studies is almost taboo, because data in these studies, e.g., survey data and resting-state neuroimaging data, are often contaminated by unmeasured confounders. Psychologists and neuroscientists are often cautious about their results, and reluctant to make false claims about causality in non-experimental studies. Therefore, they adopt less stringent statistical analysis techniques that can only infer associational relations. However, the ambiguity about causality in traditional statistical analysis creates much confusion in interpreting analytical results - some studies make implicit causal claims about their results using words such as “impacts”, “lead to” and “affects”. This …

Sentiment Analysis In Application To Behavior Prediction, Anna Singley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Getting Started Analyzing Data In Spss, Kristi Thompson

Western Libraries Presentations

SPSS is a popular package for analyzing data. This session will discuss how to get started on a simple quantitative analysis project using SPSS. Topics covered will include getting summary statistics, creating and modifying variables, creating graphs, running simple analyses, and interpreting SPSS output.

Analyzing The Production And Use Of Fossil Fuels: A Case For Data Mining And Gis, Alejandro Conde

Geography and the Environment: Graduate Student Capstones

As technology progresses and data grows both larger and more complex, techniques are being developed to keep up with the exponential growth of information. The term “data mining” is a blanket term used to describe an approach to find anomalies and correlations in a large dataset. This approach involves leveraging data mining software to manipulate and prepare data, apply statistics to quantify trends and characteristics in the data from a high level, and potentially apply advanced techniques like machine learning to identify patterns that wouldn’t be apparent otherwise. In this case study, data mining aided a GIS in displaying substantial …

Public Acceptance Of Medical Screening Recommendations, Safety Risks, And Implied Liabilities Requirements For Space Flight Participation, Cory J. Trunkhill

Doctoral Dissertations and Master's Theses

The space tourism industry is preparing to send space flight participants on orbital and suborbital flights. Space flight participants are not professional astronauts and are not subject to the rules and guidelines covering space flight crewmembers. This research addresses public acceptance of current Federal Aviation Administration guidance and regulations as designated for civil participation in human space flight.

The research utilized an ordinal linear regression analysis of survey data to explore the public acceptance of the current medical screening recommended guidance and the regulations for safety risk and implied liability for space flight participation. Independent variables constituted participant demographic representations …

The Link Between Democratic Institutions And Population Health In The American States, Julianna Pacheco, Scott Lacombe

Government: Faculty Publications

Context: This project investigates the role of state-level institutions in explaining variation in population health in the American states. Although cross-national research has established the positive effects of democracy on population health, little attention has been given to subnational units. The authors leverage a new data set to understand how political accountability and a system of checks and balances are associated with state population health. Methods: The authors estimate error correction models and two-way fixed effects models to estimate how the strength of state-level democratic institutions is associated with infant mortality rates, life expectancy, and midlife mortality. Findings: The authors …

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

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 …

“Be A Pattern For The World”: The Development Of A Dark Patterns Detection Tool To Prevent Online User Loss, Jordan Donnelly, Alan Dowley, Yunpeng Liu, Yufei Su, Quanwei Sun, Lan Zeng, Andrea Curley, Damian Gordon, Paul Kelly, Dympna O'Sullivan, Anna Becevel

Articles

Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns.

Improving Country Conflict And Peace Modeling: Datasets, Imputations, And Hierarchical Clustering, Benjamin D. Leiby

Theses and Dissertations

Many disparate datasets exist that provide country attributes covering political, economic, and social aspects. Unfortunately, this data often does not include all countries nor is the data complete for those countries included, as measured by the dataset’s missingness. This research addresses these dataset shortfalls in predicting country instability by considering country attributes in all aspects as well as in greater thresholds of missingness. First, a structured summary of past research is presented framed by a developed casual taxonomy and functional ontology. Additionally, a novel imputation technique for very large datasets is presented to account for moderate missingness in the expanded …

Analyzing Fluctuation Of Topics And Public Sentiment Through Social Media Data, Haoyue Liu

Dissertations

Over the past decade years, Internet users were expending rapidly in the world. They form various online social networks through such Internet platforms as Twitter, Facebook and Instagram. These platforms provide a fast way that helps their users receive and disseminate information and express personal opinions in virtual space. When dealing with massive and chaotic social media data, how to accurately determine what events or concepts users are discussing is an interesting and important problem.

This dissertation work mainly consists of two parts. First, this research pays attention to mining the hidden topics and user interest trend by analyzing real-world …

Developing Research Data Management Services In A Regional Comprehensive University: The Case Of Central Washington University, Ping Fu, Maurice Blackson, Maura Valentino

Library Scholarship

This study aims to analyze the needs of researchers in a regional comprehensive university for research data management services; discuss the options for developing a research data management program at the university; and then propose a phased three-year implementation plan for the university libraries. The method was to design a survey to collect information from researchers and assess and evaluate their needs for research data management services. The results show that researchers’ needs in a regional comprehensive university could be quite different from those of researchers in a research-intensive university. Also, the results verify the hypothesis that researchers in the …

Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology, Rao Hamza Ali, Amir Kanan Kashefi, Alice C. Gorman, Justin St. P. Walsh, Erik J. Linstead

Art Faculty Articles and Research

We develop and apply a deep learning-based computer vision pipeline to automatically identify crew members in archival photographic imagery taken on-board the International Space Station. Our approach is able to quickly tag thousands of images from public and private photo repositories without human supervision with high degrees of accuracy, including photographs where crew faces are partially obscured. Using the results of our pipeline, we carry out a large-scale network analysis of the crew, using the imagery data to provide novel insights into the social interactions among crew during their missions.

Estimating The Health Effects Of Adding Bicycle And Pedestrian Paths At The Census Tract Level: Multiple Model Comparison, Ross J. Gore, Christopher Lynch, Craig Jordan, Andrew Collins, R. Michael Robinson, Gabrielle Fuller, Pearson Ames, Prateek Keerthi, Yash Kandukuri

VMASC Publications

Background: Adding additional bicycle and pedestrian paths to an area can lead to improved health outcomes for residents over time. However, quantitatively determining which areas benefit more from bicycle and pedestrian paths, how many miles of bicycle and pedestrian paths are needed, and the health outcomes that may be most improved remain open questions.

Objective: Our work provides and evaluates a methodology that offers actionable insight for city-level planners, public health officials, and decision makers tasked with the question “To what extent will adding specified bicycle and pedestrian path mileage to a census tract improve residents’ health outcomes over time?” …

A Large-Scale Sentiment Analysis Of Tweets Pertaining To The 2020 Us Presidential Election, Rao Hamza Ali, Gabriela Pinto, Evelyn Lawrie, Erik J. Linstead

Engineering Faculty Articles and Research

We capture the public sentiment towards candidates in the 2020 US Presidential Elections, by analyzing 7.6 million tweets sent out between October 31st and November 9th, 2020. We apply a novel approach to first identify tweets and user accounts in our database that were later deleted or suspended from Twitter. This approach allows us to observe the sentiment held for each presidential candidate across various groups of users and tweets: accessible tweets and accounts, deleted tweets and accounts, and suspended or inaccessible tweets and accounts. We compare the sentiment scores calculated for these groups and provide key insights into the …

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 …

Legislative Language For Success, Sanjana Gundala

Master's Theses

Legislative committee meetings are an integral part of the lawmaking process for local and state bills. The testimony presented during these meetings is a large factor in the outcome of the proposed bill. This research uses Natural Language Processing and Machine Learning techniques to analyze testimonies from California Legislative committee meetings from 2015-2016 in order to identify what aspects of a testimony makes it successful. A testimony is considered successful if the alignment of the testimony matches the bill outcome (alignment is "For" and the bill passes or alignment is "Against" and the bill fails). The process of finding what …

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, …

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 …