Voting technology, democracy, and propaganda: Ontological considerations for the 2020 presidential election

The 2020 United States Presidential election was considered one of the most tumultuous political contests in the 21st century. During an international pandemic, travel restrictions and social distancing requirements created uncertainty about whether to vote in person or via absentee-mail-in ballot. The present study sought to investigate how voters experience different technologies in the 2020 United States Presidential election. Selected concepts in media ecology supplemented Fox and Alldred's (2013) framework for new materialist inquiry to explore the technical material characteristics of voting technology and the discursive elements of voter fraud propaganda. By tracing the history of voting technologies and voter fraud propaganda, the analysis argued that the vast array of technologies and experiences of voting in the 2020 election rendered the idea of an archetypal or monolithic voting method insufficient. Therefore, the present study suggests an ontological revision for the ways we conceptualize the relationship between voters, voting technologies, and democracy writ large. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Data-driven techniques for human activity sensing in smart environments

The number of Internet-of-Things (IoT) and edge devices has exploded in the last decade, providing new opportunities to sense and enable many applications to transform everyday people's lives. Wide-scale time series data collected through such devices, coupled with advances in learning technologies, can transform how people interact with their environment. However, as we enter the era of ubiquitous computing, there is a growing need for methods that are easy to use, computationally feasible, and require minimal human supervision to sense human activities by analyzing large-scale data. The goal of this research work is to propose data-driven techniques that focus on human activity sensing at different scales.The first part of the thesis focuses on human activity sensing at building scale for smart indoor environments. Towards that end, this work emphasizes general-purpose human activity sensing using ambient sensors for context-aware computing in smart environments. A deep neural network-based technique for sensing human-environment interaction is proposed and experiments explored interpretability for different ambient sensors and their contribution to model performance to avoid data redundancy. Identifying the challenge of distribution shift in long-term activity sensing, the thesis next focuses on time series partitioning for unlabeled IoT sensor streams, which is an important step toward continuous human activity sensing. This work proposes Cadence, a generalized change point detection technique that detects change points through hypothesis testing by learning a data representation specifically with the segmentation objective. Experiments show that it is sample-efficient, unsupervised, and can robustly detect time-series events across different applications while needing only 9-93 seconds for training.The second part of the thesis focuses on human activity sensing at city scale using large-scale spatio-temporal data. A framework is introduced for sensing urban activity and policy compliance during the COVID-19 crisis using vision and language-based sensing from street view images. Understanding the challenges of street view image usage in urban sensing due to its large scale and distribution variance, a data-driven framework is proposed to evaluate the quality of information in urban scale street view images based on quality attributes capturing spatial, temporal, and content information present in the data. Our experiments show that such framework can be useful for ranking, querying, and improving spatio-temporal data quality and usage in urban computing and activity sensing. We believe such techniques can be useful to model our living patterns by analyzing large-scale data and improve the quality of our life through applications such as home automation, energy optimization, and personalized healthcare. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Dialogues for equity: Precarious parent-scholars in times of crisis

ABSTRACT The COVID-19 pandemic amplified inequities around parent-scholars in the neoliberal gig academy. This paper documents the stories and intersectional struggles of four precarious parent-scholars as they navigated doctoral work, dissertation defenses, research, remote teaching, and family life during the pandemic. We illustrate how we navigated our neoliberal subjectivities and the extending multifold crises around the division of labor between academic work and parenting, gender roles, and internalized pressures exacerbated by a public postsecondary education system that exploits increasingly precarious workforces. Through critical collaborative autoethnography, we reflect on our parenting and teaching from March 2020 to August 2021. Drawing from our collective findings we summarize three mutually interdependent areas of communicative intervention that can make our workplace more equitable, entailing self-reflection, negotiation of labor, and collaborative dialogue. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

The lived experiences of selected choral directors during the COVID-19 pandemic

The shift to online education during the COVID-19 pandemic found secondary choral teachers moving traditional performance-based courses to the online venue. The pedagogical changes needed include implementing technology and disseminating information through learning management systems. Relationships between teachers and students, and teachers and colleagues, were challenged with the physical distance of quarantines in the Spring of 2020. This dissertation research project examined the difficulties six teachers faced concerning technology and relationships. I sat down for semi-structured interviews with six colleagues where I asked about their backgrounds, relationships with students and fellow colleagues, and the changes the pandemic brought to their perceptions of teaching. To conclude, I discussed the themes that arose and unexpected findings such as the importance of mental health for the educators and the change in content from curricular-driven to vital lifelines for communication during the height of the pandemic. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Teachers' perceptions on the effects of COVID-19 on juniors and seniors in high school

The purpose of this study was to examine the academic, social, and emotional effects of COVID19 on 11th - and 12th -grade students. There has been little documentation regarding the specific change that the pandemic has had on these students;it is imperative that we look at the effects of COVID-19 on the students who experienced COVID-19 pandemic. Data collection was completed through individual interviews. Analysis of data occurred in three phases: (a) categorization of data under the four organizational factors, (b) building the explanation in a phenological form, and (c) re-examination of the data. The analysis of the narrative study was based on the theoretical proposition that the teachers were focused on the whole child and not just academic standards. The humanistic theory framework was established as teachers examined the influences in their classrooms based on the well-being of their students. The credibility of the analysis was protected by triangulation of data through multiple sources of evidence, establishment of a chain of evidence, and member checking.The results revealed that the main concerns were students attending school and getting the credits needed to graduate through both in-person classes and online learning. The themes that emerged were classroom management, relationship building, communication, social-emotional learning, trauma-informed learning, and the effects of COVID-19. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

A framework to evaluate trustworthiness in online video-based information environments

Online misinformation has been shown to be a significant threat, with measurable real world impact. This has become especially evident during the COVID-19 crisis, where online spaces saw the propagation of false or inaccurate information on healthcare, protective equipment, vaccines, and more;causing major public health repercussions. Although many video-based online platforms are used as vehicles of such misinformation and are counted as some of the most popular and influential social media platforms, current research faces a lack of systemic methodology to analyze such content and detect potential misinformation efforts. This work proposes a solution by introducing an adaptable framework. This framework provides indicators of potential misinformation campaigns, addresses issues of large data volumes, and takes into consideration multiple classes of features such as media content, engagement, and user networks. The goal of this research is to integrate into larger, user-facing systems and help members of the information community, data scientists, journalists, or policy makers to make sense of impossibly large information environments and take action based on reliable data. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Leveraging behavioral data for public health: Exploring sleep and nature exposure using mobile phones and social media

Health surveillance and assessment are considered essential components of a functional public health system. The recent ubiquity of mobile devices and social media have created a wealth of behavioral data, and bring into existence new forms of population health monitoring. These new digital sources can provide direct and passive data for more detailed and nuanced health factors, and have expanded the human, spatial, and temporal scales at which these factors can be measured. In this project, I leverage digital trace data from tweets and mobile device location pings to explore population scale sleep loss, and nature exposure through park visitations in the United States. Both sleep and nature exposure are essential contributors to well-being, and have historically relied on either survey data or direct observation of individuals to measure. I begin by demonstrating the ability of Twitter data to passively reflect population-scale sleep loss at the state level. This is followed by an exploration of park visitation measured through mobile device GPS data. Changes in county-scale park visitation behavior at the onset of the COVID-19 pandemic are analyzed and comparisons are made using population density, employment sector, income, and voting records. In the final chapter I investigate the viability of predicting park visitation using demographic information from the surrounding neighborhood. I conclude with a brief discussion of the significance of measuring these behaviors, and the potential for health policy improvement. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

An NLP analysis of health advice giving in the medical research literature

Health advice - clinical and policy recommendations - plays a vital role in guiding medical practices and public health policies. Whether or not authors should give health advice in medical research publications is a controversial issue. The proponents of "actionable research" advocate for the more efficient and effective transmission of science evidence into practice. The opponents are concerned about the quality of health advice in individual research papers, especially that in observational studies. Arguments both for and against giving advice in individual studies indicate a strong need for identifying and accessing health advice, for either practical use or quality evaluation purposes. However, current information services do not support the direct retrieval of health advice. Compared to other natural language processing (NLP) applications, health advice has not been computationally modeled as a language construct either. A new information service for directly accessing health advice should be able to reduce information barriers and to provide external assessment in science communication.This dissertation work built an annotated corpus of scientific claims that distinguishes health advice according to its occurrence and strength. The study developed NLP-based prediction models to identify health advice in the PubMed literature. Using the annotated corpus and prediction models, the study answered research questions regarding the practice of advice giving in medical research literature. To test and demonstrate the potential use of the prediction model, it was used to retrieve health advice regarding the use of hydroxychloroquine (HCQ) as a treatment for COVID-19 from LitCovid, a large COVID-19 research literature database curated by the National Institutes of Health. An evaluation of sentences extracted from both s and discussions showed that BERT-based pre-trained language models performed well at detecting health advice. The health advice prediction model may be combined with existing health information service systems to provide more convenient navigation of a large volume of health literature. Findings from the study also show researchers are careful not to give advice solely in s. They also tend to give weaker and non-specific advice in s than in discussions. In addition, the study found that health advice has appeared consistently in the s of observational studies over the past 25 years. In the sample, 41.2% of the studies offered health advice in their conclusions, which is lower than earlier estimations based on analyses of much smaller samples processed manually. In the s of observational studies, journals with a lower impact are more likely to give health advice than those with a higher impact, suggesting the significance of the role of journals as gatekeepers of science communication.For the communities of natural language processing, information science, and public health, this work advances knowledge of the automated recognition of health advice in scientific literature. The corpus and code developed for the study have been made publicly available to facilitate future efforts in health advice retrieval and analysis. Furthermore, this study discusses the ways in which researchers give health advice in medical research articles, knowledge of which could be an essential step towards curbing potential exaggeration in the current global science communication. It also contributes to ongoing discussions of the integrity of scientific output.This study calls for caution in advice-giving in medical research literature, especially in s alone. It also calls for open access to medical research publications, so that health researchers and practitioners can fully review the advice in scientific outputs and its implications. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Whose future? Whose facts?: A critical case study of news literacy education in the United States

In the wake of the 2016 and 2020 U.S. presidential elections and the COVID-19 pandemic, increasing public attention has been paid to the ability of citizens to use and understand news media, information, and digital technology. Conversations about media literacy-the ability to critically engage with media-are ongoing in the press, schools, and state and federal governments. Most media literacy scholars agree that media literacy is an integral part of an informed and healthy democracy. Yet not all media literacy approaches are the same, and some scholars suggest that mainstream approaches may re-create antidemocratic systems and ideologies. What does it mean when the tools intended to support a healthy democracy reinforce systems of oppression?A case study of the News Literacy Project (NLP), a nonpartisan, nonprofit education organization, was used to explore this question by examining how ideologies of racism and neoliberal capitalism are perpetuated or challenged in the resources and curriculum created and disseminated by NLP, which positions itself as a leader in news literacy education. Within a theoretical framework of critical political economy of communication, curriculum theory, and Critical Race Theory, NLP as an organization and its Checkology curriculum were analyzed to understand how ideologies of racism and neoliberal capitalism are replicated or rejected in this curriculum. NLP depends on corporate and philanthropic funding from both media and nonmedia industries and uses the standards of the professional news industry to define its approach to news literacy education. The Checkology 101 curriculum, a default set of news literacy lessons available through an online portal, reflects ideologies of neoliberal capitalism through its atomized and individualistic structure, limited critiques of the news industry's economic structures, and language centered on individualism and consumerism. The curriculum also reflects ideologies of racism, which appear to be the unintentional result of reliance on liberal ideals such as aspirations for neutrality, universality, objectivity, and unbiased truth, that manifest in stereotyping, decontextualized information, and incomplete storytelling. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Strategies and effectiveness of the chinese government debunking covid-19 rumors on sina weibo: Evaluating from emotions

The Chinese government refuted rumors on social media for infodemic management when COVID-19 outbroke. This study selected 80 government accounts on Sina Weibo and collected 501 valid anti-rumor posts with comments from 18 January to 29 February 2020. This paper evaluated the effectiveness of rumor debunking from the public emotions reflected in the comments. This study also examined the influence of different anti-rumor strategies, such as fact-checking, rumor response modes, and presentation forms, on the effectiveness of rumor debunking. The findings revealed that fact-checking, combined response mode and text presentation could improve the effectiveness of rumor debunking to some extent. Further analysis of the public emotions indicated a correlation between the trust in government and the effectiveness of rumor debunking. These findings suggested building a multiparticipant response mechanism with medical institutions and media to mitigate the COVID-19 infodemic through targeted strategies, thus further increasing the government's credibility via information governance. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Deconstructing the digital divide: The geography, demography, and spatial dependence of internet stability in the U.S

Internet access and connectivity has become a crucial issue of public policy across the globe. During the COVID-19 pandemic, as individuals and households transitioned to remote work and learning, usage of and strain on home networks increased dramatically. The ability to interact with the internet is quickly becoming recognized worldwide as a determinant of social, economic, and even physiological well-being. With the continuing increase in usage of telehealth, remote work & learning, and distance collaboration tools, the importance of internet access is underwritten by assumptions regarding the internet's stability of connection. A broadly accepted metric to ascertain two-way video & audio stability is known as latency. Being able to empirically and visually describe the geographic distribution of latency across spatial units is of critical importance to understanding where potential policy interventions or government assistance programs are most needed. Similarly, understanding the spatial landscape of latency reveals inequities between socioeconomic, racial, and regional populations. In order to create the most nuanced, empirically sound predictive models to understand factors that influence latency, local regression techniques must be brought to bear. In this paper, I combine a rigorous exploration of the literature with a variety of empirical tools to solve these challenging issues by examining latency across all census tracts in the United States. Quantitative techniques included in this examination are: traditional univariate, bivariate, and multivariable statistical methods, cartographic transformations, exploratory spatial data analysis, autocorrelation analyses, spatial demographic methods, local regression modeling, geographic interpolation, and kriging. I find that rural census tracts, and tracts with higher poverty rates, particularly those with populations other than non-Hispanic White, experience poorer internet stability. I provide identifiable visualizations for where latency is at its best and worst. I classify and specifically identify typologies of neighborhoods to explicitly show discrete groups of census tracts where policymakers can plan interventions. Finally, I present kriging as a methodological tool to predict previously unknown values of latency in order to better fill in the gaps of coverage areas and stability measurements. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Quantitative methods for improving medical decision-making

Innovation in causal inference and implementation of electronic health record systems are rapidly transforming medical care. In this dissertation, we present three examples in which use of methods in causal inference and large electronic health record data address existing challenges in medical decision-making. First, we use principles of causal inference to examine the structure of randomized trials of biomarker targets, which have produced divergent results and controversial clinical guidelines for management of hypertension and other chronic diseases. We discuss four key threats to the validity of trials of this design. Second, we use methods in causal inference for adjustment of time-varying confounding to estimate the effect of time-varying treatment strategies for hypertension. We report the results of a study which used longitudinal electronic health record data from a prospective virtual cohort of veterans. Third, we use individual-level electronic health record data to predict the need for critical care resources during surges in COVID-19 cases, to aid hospital administrators with resource allocation in periods of crisis. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Human welfare & emergencies: Education, natality, and violence

I identify changes in human action during emergencies such as heavy precipitation and shelter-in-place orders. In two chapters I explore the effects of precipitation on educational attainment and birth rates as residential broadband access increases. In my third chapter I identify the movement of pets in and out of the home as a trigger for domestic violence during the COVID-19 lockdown. I estimate difference-in-difference regressions with panel data, coming to three conclusions. First: educational attainment in Appalachia is stunted by precipitation, as students have difficulty getting to school in bad weather. As this historically under-educated region of the US gains internet access, the negative effects of rain and snow disappear. Second: there is little evidence that precipitation increases natality. What little evidence of this "blizzard baby" phenomenon I do find is negated by mobile internet access, which decreases births nine months after high precipitation. Third: during COVID-19 shelter-in-place orders, domestic violence decreases after pets are surrendered to local shelters and increases when pets are confiscated. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Maternal technology distraction and its associations with stress and parenting during the COVID-19 pandemic

The widespread adoption of digital technology devices has introduced unique challenges to modern parenthood, especially during the COVID-19 pandemic when parents relied on digital technology more than ever before. Parents have experienced significant challenges during the COVID-19 pandemic, with mothers being especially vulnerable to stress and mental health problems. This study investigates associations between technology distraction of mothers while spending time with their offspring, psychological well-being (stress sensitivity), and parenting behaviors (warmth and indifference) during the COVID-19 pandemic. Mothers (n = 246) of adolescents (aged 13-18) who attended public secondary schools in Italy completed an online survey during the fourth wave of COVID-19. The pattern of associations was analyzed via path analysis. COVID-19 pandemic-induced stressors were positively associated with perceived stress, which was positively associated with technology distraction of mothers when spending time with their offspring. Furthermore, maternal technology distraction was positively associated with indifference and negatively associated with warmth. Perceived stress was negatively associated only with warmth. Strategies to mitigate stress during times of crisis and adversity might be useful for potentially vulnerable targets (e.g., mothers living with offspring during the COVID-19 pandemic). Information and prevention actions should be focused on how parents use digital devices while with their offspring. (PsycInfo Database Record (c) 2023 APA, all rights reserved) Impact Statement This study examined potential correlates of maternal technological distraction while mothers spent time with their offspring during the COVID-19 pandemic. Results indicate that COVID-19-specific effects on life dimensions (e.g., relationships with family members/friends, work performance, family financial situations) were associated with high perceived stress, which was associated with greater technology distraction of mothers when spending time with their offspring. Furthermore, maternal technology distraction was linked to negative parental behaviors (higher indifference and lower warmth), suggesting the relevance of using strategies to mitigate stress in potentially vulnerable persons during times of crisis such as the pandemic context. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Communicating veracity: The impact of emotion and multimodal resources for correcting online misinformation in older adults

This dissertation research project explored the impact of emotion (positive or negative) and presentational modality (text-only, multimodal, motion imbued styles) in correcting online misinformation for older adults. Using the theoretical foundation of the heuristic and systematic processing model, along with the emotion-based broaden and build and socioemotional selectivity theories, participants (N=302), in an online experiment, were exposed to social media misinformation rebuttals for two topics: that vaccines cause magnetism and COVID can be cured through the intake of vitamin supplements (such as Vitamin C or D). Results showcased the effectiveness of crafting positively framed misinformation corrections for the bolstering of message credibility within typically incongruent ideological groups, and in the use of motion within correctional content for the elevation of positive affect. Additionally, this study also exposed a link between medical mistrust and the perceived credibility toward vaccine and COVID-19 misinformation corrections, a reminder for health communication practitioners of the underlying political factors behind belief in health misinformation. Lastly, results from a thought-listing exercise displayed the prominence of heuristic thinking styles with rare exceptions for systematic processing spurned by skepticism and a desire to preserve original vaccination and COVID-19 beliefs. For scholars and practitioners, results, in general, point to a de facto reliance on heuristic cues in the evaluation of online information, with important considerations for systematic processing, and two, the use of positive affect in aiding the acceptance of misinformation corrections that may run counter to the beliefs of your target audience. This lends credibility to theories that prioritize the use of positive emotion for bolstering message reception and effectiveness for older adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

"Whatsapp, God?" A comparative analysis of intercessory prayer by ICGC members on whatsapp and in-person congregational settings in Accra, Ghana

Intercessory prayer remains an integral part of Ghanaian Christians'social lives. However, the COVID-19 pandemic disrupted regular in-person congregational intercessory prayer meetings in the country of Ghana. Rather than abandoning the practice of intercessory prayer, churches such as the International Central Gospel Church (ICGC) used chat messenger apps like WhatsApp to leap over the disrupted activities of in-person congregational meetings. This research employed an exploratory sequential mixed-methods approach and the Uses and Gratification Theory and Theological Acceptance Model as its theoretical frameworks to ascertain whether ICGC members consider WhatsApp to be more efficacious than in-person congregational settings for intercessory prayer. The results from 330 ICGC members revealed that ICGC members prefer in-person congregational meetings to WhatsApp for intercessory prayer and augment their intercessory prayer experience with WhatsApp based on the context. WhatsApp, in this regard, is an alternative tool and not a replacement for in-person intercessory prayer. The study provides a spiritual motivations perspective to the Uses and Gratification theory. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Exploring the audiovisual effects on sport viewer satisfaction through the lens of the psychological continuum model

As the source of one of the largest revenue streams for professional sport franchises, the viewership of sport broadcasts has plummeted in recent years (Bode, 2018). This declining trend has been further exacerbated by the global COVID-19 pandemic (Crupi, 2021). According to Deloitte's Fan Engagement survey, the average fan satisfaction across sports broadcast programs was only 39 percent (Deloitte, 2019).Research has been devoted to investigating the determinants of sport viewer satisfaction, including various audio and visual conditions of sport broadcasts. However, these works assume that media design effects are equally effective among all viewers and fail to account for potential heterogeneities in people's psychological connection to the mediated sport. To address this gap, the Psychological Continuum Model (PCM;Funk & James, 2001;2006) was introduced as the theoretical foundation for understanding the formation of viewer satisfaction with a focal sport (e.g., college football).The current dissertation examines whether and how the strength of psychological connection to college football overrides the effects of varying audiovisual presentations on viewer satisfaction with a televised college football game. A 2 (presence of commentary: With commentary vs. Without commentary) x 2 (presence of audience: High vs. Low) between-subjects online experiment was administered via Prolific (n = 338). The relationship between psychological connection and viewer satisfaction and the moderation effects of the two selected audiovisual conditions were tested using the ANCOVA. Results showed a significant positive association between psychological connection to college football and viewer satisfaction. However, the manipulated audiovisual conditions did not moderate the aforementioned relationship between psychological connection and viewer satisfaction. The presence of audience had a significant positive effect on viewer satisfaction. In contrast, the presence of commentary exerted no significant effect on viewer satisfaction regardless of people's PCM staging.The findings provide empirical evidence to support the seminal PCM framework that the strength of an individual's psychological connection to the focal sport object was a more deterministic factor that drives the sport media consumption experience than the audiovisual media presentation. For those interested in watching but have not yet formed a strong attitude towards the broadcasted sport object, the viewing experience can be optimized by maximizing the visual presence of a live audience. The null effect of commentary presence and sonic ambiance on viewer satisfaction reinforces the proposition that what is seen might be more influential than what is heard in sport media consumption (Cummins et al., 2019). (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Online misinformation harms on social media during crises: Misinformation harm types, perceptions, antecedents, and effects toward misinformation sharing

During humanitarian crises like natural disasters, manmade crises, health crises or several complex crises, people are motivated to seek for a large amount of information in a limited time to make proper important decisions. Social media platforms can support quick crisis communication but can also be subject to harmful misinformation or false claims. To contribute to efforts facing harms from crisis misinformation, this dissertation includes three essays that investigates different aspects of misinformation harms such as different types or dimensions of harms and causalities surrounding the harms.The first essay draws insights from previous related studies about the harms of consuming information to develop a taxonomy of both short-term and long-term crisis misinformation harms, including 15 types of harms grouped in 8 categories such as physical or psychological harms. Such taxonomy was then validated in two misinformation scenarios related to healthcare crisis and natural disaster, and through a post hoc analysis of different groups of participants. The second essay develops a mechanism to quantify health crisis misinformation harms from 6 COVID-19 pandemic misinformation scenarios. The mechanism addresses perceptions of crisis misinformation harms captured by a survey in two categories of harms, comparative harms (including component harms and contextual harms based on specific contexts) and noncomparative harms (counter-contextual harms based on counterfactual comparisons of different contexts), with significant differences between the pandemic victims and nonvictims. Concerning about 10 COVID-19 vaccine misinformation, the third essay includes two rounds of a longitudinal survey investigates the causality surrounding misinformation harms with certain antecedents (like trust and science attitudes) and the effects on misinformation sharing decisions. In summary, the dissertation aims to examine the under-addressed phenomenon of crisis misinformation harms, to contribute to the literature of crisis communication, to support efforts confronting misinformation diffusions, and to help optimize emergency responses related to misinformation harms. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Racism and resilience of pandemic proportions: Online harassment of asian americans during covid-19

ABSTRACT This study explores perceptions of online racial hate speech directed at Asian Americans in the United States during the COVID-19 pandemic. We examined how individuals' enactment of resilience communication in response to that threat affected their self-reported estimates of personal health. Using a nationally representative survey (n = 1767) that oversampled Asian Americans (n = 455), we found that Asian Americans perceived the problem of online hate speech to be more severe than members of non-targeted groups. Analysis revealed a mediated pathway through which heightened perceptions of online racial hate speech were positively associated with individuals' enactment of specific resilience processes tied to identity affirmation, which was linked to positive gains in psychological health. Results contribute to resilience theory in the context of racism and the observed relationships between resilience communication and health. We discuss how individuals in minoritized communities and allies might use resilience to combat the synergistic stressors of the COVID-19 pandemic. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Addressing cyber deception and abuse from a human factors perspective

The role of technology has undoubtedly evolved into amplifying attackers' ability to use the cyber space for the deceit and abuse of Internet users. This dissertation seeks to investigate these problems from the lens of deceptive and abusive content (e.g., phishing, social engineering, dis- or misinformation, intimate partner surveillance). Phishing is an extremely popular cyber-social engineering attack that come with great costs to society-at-large, and along with mis- and disinformation, has risen to society's collective consciousness after the 2016 and 2020 U.S. General Elections, as well as the onset of the COVID-19 pandemic. Furthermore, research into crimes of abuse surrounding intimate partner violence (IPV), colloquially known as domestic abuse, is still in its infancy, yet IPS allows abusers to stalk, monitor, intimidate, and harass their victims as a form of further control. This thesis seeks to tackle these issues through a multi-methods approach, including natural language processing to detect the presence of influence cues in text, qualitative methods, and rigorous statistical analyses. I detail how cyber abuse is leveraged in social media, how expert advice can negative affect minorities, and investigate how subtle online toxicity can be automatically detected. I then investigate several different ways to mitigate the harms of online deception. The work detailed in this dissertation has resulted in novel and publicly available datasets that may pave the way for further novel mitigations and solutions within their fields and to the global problem of cyber deception and abuse. (PsycInfo Database Record (c) 2022 APA, all rights reserved)