500 Days of Summer, released in 2009 and written by Scott Neustadter and Michael H. Weber, is an American film told through the perspective of Tom Hansen, the male lead. It is a story that begins with a third-person narrator, explaining that “This is a story of boy meets girl.” The narration then finishes with a warning that “you should know up front, this is not a love story” (Neustadter & Weber, 2009). As the movie continues, however, it becomes increasingly challenging to believe this warning. Tom sees Summer Finn, falls in love, and their relationship ends with him broken-hearted. It is only natural for the audience to view it as a story of Tom’s failed love, and without a deeper analysis, to perceive Summer as the antagonist. <br/> This tendency to view the movie as a love story motivated me to question why the discrepancy between the beginning narration and the common audience perception occurs. My thesis addresses this discrepancy by focusing on the idea that the natural gravitation towards the belief that 500 Days of Summer is a love story exists due to the unreliable narration given by Tom Hansen throughout the movie. I wrote three songs, an interlude, a duet, and a solo, based on the themes and lead characters of the movie to help validate the warning provided in the beginning and provide a deeper insight into Summer’s version of the story.

The COVID-19 pandemic began in March of 2020 and drastically affected the global human population. Millions of people died due to a SARS-CoV-2 infection while many who survived developed devastating sequelae of the disease. In addition, the closure of schools and businesses led to international economic struggle in the year 2020 as global economies declined. Since the beginning of the pandemic, over 200,000 scientific articles have been published and compiled into a database that grows daily— a rare occurrence within the scientific community. This thesis uses natural language processing tools via Python and VOSviewer software to perform a bibliometric analysis on 205,712 papers published between January of 2020 and February of 2021 pertaining to COVID-19. We first investigate how to analyze these publications most effectively in terms of title versus abstract keyword searches, we further obtain the focus of the current scientific literature via co-occurrence analysis and clustering, and we at last discuss the time evolution of these topics over the course of 14 months.