Misinformation, defined as incorrect or misleading information, has been around since the beginning of time. However, the rise of technology and widespread use of social media has allowed misinformation to evolve and gain more traction. This study aims to examine health and political misinformation within the contexts of the COVID-19 pandemic and the 2020 U.S. Presidential Election. Utilizing samples of misinformation from the 45th president of the United States, I analyzed the levels of engagement that this misinformation received on the social media platform X, formerly known as Twitter. I also examined how various Google search query trends changed over time in response to this misinformation. Then, I categorized the data into misleading statistics, misrepresentations of opinions as facts, or completely false content. Lastly, I looked into the physical responses that resulted from the spread of such misinformation. My findings of this case study showed that misinformation received significantly more attention than other social media posts, as evidenced by increased Google searches related to the topics and higher levels of likes and retweets on misinformative Tweets during the specified periods. Furthermore, the former president employed all three types of misinformation, with misleading statistics most prevalent in the health misinformation sample and misrepresentations of opinions as facts most prevalent in the political misinformation sample. The repercussions of this misinformation encompassed individuals ingesting unsafe products, decreased trust in the electoral process, and a violent insurrection at the U.S. Capitol. Despite the existing research in this field, there remains much more to be uncovered regarding the vast amount of misinformation circulating on the Internet.

How is knowledge created at the intersections between basic science, biotechnology, and industry? Gene drives are an interesting example, as they combine a long-standing interest with a recent technological breakthrough and a new set of commercial applications. Gene drives are genes engineered such that they are preferentially inherited at a frequency greater than the typical Mendelian fifty percent ratio. During the historical and conceptual evolution of gene drives beginning in the 1960s, there have been many innovations and publications. Along with that, gene drive science developed considerable public attention, explosion of new scientists, and variation in the way the topic is discussed. It is now time to look at this new organization of science using a systematic approach to characterize the system that has enabled knowledge to grow in this scientific field. This project breaks new ground in how knowledge advances in genetic engineering science, and how scientists understand what a “gene drive” is through analysis of language, communities, and other social factors. In effect, this research will advance multiple fields and enable a deeper understanding of knowledge and complexity. This project documents patterns of publication, collaborative relationships, linguistic variation, innovation, and knowledge expansion. The results of computational analysis provide an in-depth and complete characterization of the structure, dynamics, and evolution of scientific knowledge found in the gene drive technology. Further, time series analysis of the multiple layers of discourse enabled a diachronic connective mapping of collaborative relationships and tracked linguistic variation and change, highlighting where ambiguous language may appear, improving and creating more cohesive scientific language. Overall, depicting the structure, dynamics, and evolution of scientific knowledge during a novel eruption of scientific complexity can shed light on the factors that can lead to: (1) improved scientific communication, (2) reduction of scientific progress, (3) new knowledge, and (4) novel collaborative relationships. Therefore, characterizing the current technological, methodological, and social contexts that can influence scientific knowledge.

This dissertation looks at two works of nineteenth-century British fiction that are considered outliers: Sir Walter Scott's Saint Ronan's Well (1824) and George Eliot's "The Lifted Veil" (1859). Saint Ronan's Well, a work of domestic fiction, has long been described as unusual for Scott because it is unlike his signature historical novels. "The Lifted Veil,” a Gothic novella, is generally understood as different in kind from Eliot’s realist and social problem fiction. I describe both texts as outliers because they have been described as atypical (in the case of Eliot) or less worthy of study (in the case of Scott) by scholars, for myriad reasons. My work uses both computational methods and tools and traditional literary close readings to test and assess these outlier works. I use stylometry, a computational tool that reads and compares texts to determine authorship attribution, to determine if both texts are indeed outliers for these authors. In addition, I use stylometric methods to analyze claims made by initial reviewers and contemporary critics about comparative authors and genres for Saint Ronan's Well and "The Lifted Veil." I examine statistical or stylistic evidence to test whether those long-standing claims of literary difference are supported with computational evidence. Each chapter consists of a series of stylometric tests that are analyzed in conjunction with close readings of text. The dissertation reaches three conclusions, based on the results of stylometric tests described across its four chapters. First, I find that, although Saint Ronan's Well is written in a unique subgenre for Scott, it is statistically and stylistically similar to his other novels. Second, I argue that "The Lifted Veil" is both an outlier for Eliot and an outlier among canonical work of the period in general, as indicated by the results of several stylometric tests. Finally, I argue that focusing on literary outliers is a necessary and productive step forward for traditional and computational literary studies. Focusing on texts that are literary and statistical outliers shows how computational and traditional literary methods can blend together to test the extent of generalizable knowledge in literary studies, especially with nineteenth-century British fiction.

Referring Expression Comprehension (REC) is an important area of research in Natural Language Processing (NLP) and vision domain. It involves locating an object in an image described by a natural language referring expression. This task requires information from both Natural Language and Vision aspect. The task is compositional in nature as it requires visual reasoning as underlying process along with relationships among the objects in the image. Recent works based on modular networks have

displayed to be an effective framework for performing visual reasoning task.

Although this approach is effective, it has been established that the current benchmark datasets for referring expression comprehension suffer from bias. Recent work on CLEVR-Ref+ dataset deals with bias issues by constructing a synthetic dataset

and provides an approach for the aforementioned task which performed better than the previous state-of-the-art models as well as showing the reasoning process. This work aims to improve the performance on CLEVR-Ref+ dataset and achieve comparable interpretability. In this work, the neural module network approach with the attention map technique is employed. The neural module network is composed of the primitive operation modules which are specific to their functions and the output is generated using a separate segmentation module. From empirical results, it is clear that this approach is performing significantly better than the current State-of-theart in one aspect (Predicted programs) and achieving comparable results for another aspect (Ground truth programs)

Cities are living systems. Their form and function are constantly changing to reflect the preferences and needs of their residents. One process of change in a city occurs when rapid investment pours into a neighborhood that was previously neglected. This so-called revitalization serves as a catalyst for many city improvements like new residential buildings, glamours commercial complexes, and even enhanced public transit. This process, also known as gentrification, can be a force for good as it results in population growth and economic opportunity. But with enough investment, prices -- including rent -- can be forced upwards equally as rapid. This is when gentrification can result in potentially negative outcomes for residents who can not keep up with the rent increases and are displaced from a city. Culture, as defined by people and business in an area, is the pride of many cities. A loss of culture through displacement is an outcome that anti-gentrification advocates want to avoid. But, cultural displacement may not always comprise a loss. In certain cases, displacement is just the natural byproduct of city evolution. An ideal solution to this state of affairs would be for cities to encourage gentrification while discouraging displacement. This study will explore how.

The sport of Ultimate, formerly known as Ultimate Frisbee™, spread around the world in the mid-seventies and was considered an alternative sport that embraced a more casual atmosphere than other traditional, competitive sports. Ultimate is now receiving national and international attention as a competitive sport, with broadcasts of games on networks such as ESPN. As it transitions into a mainstream sport while attempting to maintain its alternative roots, it is possible that there are contrasting opinions between those who want to bring it further into the mainstream and those who want to maintain as much as possible of the original, alternative culture. In this work, we surveyed members of the Ultimate community for their perspectives on the unique culture of Ultimate.
Because the Ultimate community considers itself to be progressive, despite its largely Caucasian makeup, one topic of exploration was the political landscape of the Ultimate community. A second unique aspect of ultimate is the system for enforcing rules used by the players on the field, known as the spirit of the game. This system replaces referees and creates an ethical dynamic both during play and within the community that is not found in other sports. The last major topic of study here is the self-perception of the players as athletes. Because Ultimate continues to maintain a reputation as an alternative sport, athletes may perceive themselves differently than in more established sports.
When asked if Ultimate players perceived the Ultimate community as accepting of athletes who are people of color (POC) or members of the lesbian, gay, bisexual, or transgender community (LGBT), the community reported being accepting of all minorities. However, acceptance of POC athletes was rated significantly lower than the acceptance of LGBT athletes. When asked about comradery, the respondents rated comradery higher within the Ultimate community than in other sports. When asked how impartial players were in Ultimate compared to other sports, players with more experience tended to report perceiving themselves as more impartial. All demographics reported being more impartial in Ultimate than in other athletics. When asked about the seriousness of Ultimate, those who had not played another sport considered Ultimate to be more serious than those who had played another sport. In addition, players with more years of Ultimate experience also considered it to be more serious than those with fewer years of experience. Overall, additional studies on Ultimate culture are needed in order to obtain more viewpoints, as there is a lack of research in this field for comparison.

Understanding changes and trends in biomedical knowledge is crucial for individuals, groups, and institutions as biomedicine improves people’s lives, supports national economies, and facilitates innovation. However, as knowledge changes what evidence illustrates knowledge changes? In the case of microbiome, a multi-dimensional concept from biomedicine, there are significant increases in publications, citations, funding, collaborations, and other explanatory variables or contextual factors. What is observed in the microbiome, or any historical evolution of a scientific field or scientific knowledge, is that these changes are related to changes in knowledge, but what is not understood is how to measure and track changes in knowledge. This investigation highlights how contextual factors from the language and social context of the microbiome are related to changes in the usage, meaning, and scientific knowledge on the microbiome. Two interconnected studies integrating qualitative and quantitative evidence examine the variation and change of the microbiome evidence are presented. First, the concepts microbiome, metagenome, and metabolome are compared to determine the boundaries of the microbiome concept in relation to other concepts where the conceptual boundaries have been cited as overlapping. A collection of publications for each concept or corpus is presented, with a focus on how to create, collect, curate, and analyze large data collections. This study concludes with suggestions on how to analyze biomedical concepts using a hybrid approach that combines results from the larger language context and individual words. Second, the results of a systematic review that describes the variation and change of microbiome research, funding, and knowledge are examined. A corpus of approximately 28,000 articles on the microbiome are characterized, and a spectrum of microbiome interpretations are suggested based on differences related to context. The collective results suggest the microbiome is a separate concept from the metagenome and metabolome, and the variation and change to the microbiome concept was influenced by contextual factors. These results provide insight into how concepts with extensive resources behave within biomedicine and suggest the microbiome is possibly representative of conceptual change or a preview of new dynamics within science that are expected in the future.

"On Music Videos" is an exploration of music videos, particularly narrative ones. As such, a brief history of the music video and its genres are examined. Ideas about narrative are also discussed through descriptions of what is meant by "story," based on theories from Pixar animators as well as author J.R.R. Tolkien. The connections between how story fits with music videos is then outlined. From this background research one is able to analyze examples of existing narrative music videos, before applying this knowledge and reflecting on the process of creating a narrative music video.