Purpose: Adolescent school dropout remains a major concern in the United States, accounting for 5.3% of the entire high school students in 2022. This study aims to investigate the relationships between socioeconomic status (SES), the availability of mental health and substance use treatment facilities, and school dropout rates across thirteen states.
SAFETI is the first Mason–DOLI Innovation Lab initiative that turns more than 15 years of detailed Virginia workplace-accident records into forward-looking, preventive insights. Using predictive models, the computational approach developed for SAFETI estimates the likelihood of a fatality occurring within a specific time frame and sector, along with its associated probability. This shift from reactive to preventive measures is enabled by advanced spatio-temporal and predictive analytics.
Online videos such as those streamed through YouTube are largely produced by individual users rather than traditional mass media, partly due to the incentive structure of the platforms. As part of the strategy to increase the audience, many content creators collaborate with other creators to attract subscribers and diversify their content. This behavior can be conceptualized as “coopetition” as they cooperate for their channels’ success while competing with one another for the limited pool of audience.
To understand issues about information accessibility within communities, research studies have examined human, social, and technical factors by taking a sociotechnical view. While this view provides a profound understanding of how people seek, use, and access information, this approach tends to overlook the impact of the larger structures of information landscapes that constantly shape peoples access to information.
Neighborhoods are vaguely defined, localized regions that share similar characteristics. They are most often defined, delineated, and named by the citizens that inhabit them rather than municipal government or commercial agencies. The names of these neighborhoods play an important role as a basis for community and sociodemographic identity, geographic communication, and historical context.
This research will develop a foundational tool for understanding how civic technologies are used and how information inequalities manifest in a city. User data from new civic technologies that reveal inequalities in the information environments of citizens has only recently become available. Since a large portion of data is demographically or geospatially biased due to varying human-data relationships, computational social scientists have used data modeling and algorithmic techniques to adjust the data and remove biases during data-processing.
The Cycle Atlanta project aims at creating sensor systems that allow a bike to "see" its environment and collect data as a participatory effort so that we can help the City of Atlanta to make informed decisions about biking infrastructures. Specifically, a sensor box equipped with sonars, lidars, PM sensors, gas sensors, gyroscope, accelerometer, and others was developed to detect environmental factors that can give rise to cyclists' stress level. I participated in this project as a Data Science for Social Good (Atlanta's DSSG) Summer fellow in 2017.
"Poverty maps" are designed to simultaneously display the spatial distribution of welfare and different dimensions of poverty determinants. The plotting of such information on maps heavily relies on data that is collected through infrequent national household surveys and censuses. However, due to the high cost associated with this type of data collection process, poverty maps are often inaccurate in capturing the current deprivation status.
In a creative process, divergent thinking needs to be stimulated to generate novel ideas; yet these ideas must be synthesized to produce something valuable. Hence to foster creativity in developing IT products, creators need to manage the tension between novelty and value. Since the forces affecting the novelty-value tension often exist outside a creator's group or organization, we apply organizational ecology theory to propose an industry-level, ecological model for understanding the novelty of IT products.
This project was conducted in 2008 for my bachelor's thesis in the Department of Electrical Engineering at Seoul National University (it was more like a capstone project rather than a thesis, since the focus of the project was mainly at implementing algorithms rather than analyzing the performance of algorithms using concrete measures, e.g., recall and precision). I implemented an image retrieval system prototype that takes an image as input, and outputs most similar images from the image database.