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Full-Text Articles in Social and Behavioral Sciences

Assessing The Health Effects Of Climate Change, Social Vulnerability, And Environmental Justice In Camden County, New Jersey, Daniil Ivanov Dec 2022

Assessing The Health Effects Of Climate Change, Social Vulnerability, And Environmental Justice In Camden County, New Jersey, Daniil Ivanov

Theses

Climate change negatively impacts health, while socially vulnerable and overburdened communities disproportionately experience climate change and negative health determinants. Camden County is used as a case study for analyzing environment, socioeconomics, and health. Environmental variables—PM2.5 and land cover of impervious surfaces, floodplains, and forests—were compared to the CDC Social Vulnerability Index (SVI) at the census tract level, finding significant correlations between land cover, air quality, and the SVI. The overburdened communities defined by the NJ Environmental Justice Law experienced a significantly higher incidence of emergency department visitation for respiratory, circulatory, and mental illnesses than non-overburdened communities. Health outcomes were compared …


Analyzing Fluctuation Of Topics And Public Sentiment Through Social Media Data, Haoyue Liu Aug 2022

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 …


Understanding The Voluntary Moderation Practices In Live Streaming Communities, Jie Cai May 2022

Understanding The Voluntary Moderation Practices In Live Streaming Communities, Jie Cai

Dissertations

Harmful content, such as hate speech, online abuses, harassment, and cyberbullying, proliferates across various online communities. Live streaming as a novel online community provides ways for thousands of users (viewers) to entertain and engage with a broadcaster (streamer) in real-time in the chatroom. While the streamer has the camera on and the screen shared, tens of thousands of viewers are watching and messaging in real-time, resulting in concerns about harassment and cyberbullying. To regulate harmful content—toxic messages in the chatroom, streamers rely on a combination of automated tools and volunteer human moderators (mods) to block users or remove content, which …


Towards Practicalization Of Blockchain-Based Decentralized Applications, Songlin He May 2022

Towards Practicalization Of Blockchain-Based Decentralized Applications, Songlin He

Dissertations

Blockchain can be defined as an immutable ledger for recording transactions, maintained in a distributed network of mutually untrusting peers. Blockchain technology has been widely applied to various fields beyond its initial usage of cryptocurrency. However, blockchain itself is insufficient to meet all the desired security or efficiency requirements for diversified application scenarios. This dissertation focuses on two core functionalities that blockchain provides, i.e., robust storage and reliable computation. Three concrete application scenarios including Internet of Things (IoT), cybersecurity management (CSM), and peer-to-peer (P2P) content delivery network (CDN) are utilized to elaborate the general design principles for these two main …


Representation Learning In Finance, Ajim Uddin May 2022

Representation Learning In Finance, Ajim Uddin

Dissertations

Finance studies often employ heterogeneous datasets from different sources with different structures and frequencies. Some data are noisy, sparse, and unbalanced with missing values; some are unstructured, containing text or networks. Traditional techniques often struggle to combine and effectively extract information from these datasets. This work explores representation learning as a proven machine learning technique in learning informative embedding from complex, noisy, and dynamic financial data. This dissertation proposes novel factorization algorithms and network modeling techniques to learn the local and global representation of data in two specific financial applications: analysts’ earnings forecasts and asset pricing.

Financial analysts’ earnings forecast …