This paper will analyze the two films Mississippi Burning and BlacKkKlansman, as well as some of the historical contexts surrounding them, in order to unpack the various aspects of police brutality, protest culture, and ideals of reform shown within. Furthermore, it will investigate the impact of diverging from history on the perception of policing units, and the importance of more accurate narratives like BlacKkKlansman in popular culture. <br/> To find evidence that BlacKkKlansman is a much more accurate narrative regarding law enforcement and the effects that sentiments seen in Mississippi Burning have on modern day events, a comprehensive research analysis was conducted. Both films were watched multiple times and analyzed thoroughly, and further research was done to understand not only the narrative elements of the plot, but how the visual aspects strengthen the arguments both films try to make. Scholarly articles on contexts surrounding the subjects of the film were also analyzed, including topics on the FBI, Martin Luther King Jr, and police brutality. Through this, it became evident that Mississippi Burning overlooked most of the reality of the events the film is loosely based upon in order to present a white savior story, whereas BlacKkKlansman addresses the existing prejudices head on while also showing the relation the events have to a more modern context, specifically surrounding the Trump administration.

Secure Scuttlebutt is a digital social network in which the network data is distributed among the users.<br/>This is done to secure several benefits, like offline browsing, censorship resistance, and to imitate natural social networks, but it comes with downsides, like the lack of an obvious implementation of a recommendation algorithm.<br/>This paper proposes Whuffie, an algorithm that tracks each user's reputation for having information that is interesting to a user using conditional probabilities.<br/>Some errors in the main Secure Scuttlebutt network prevent current large-scale testing of the usefulness of the algorithm, but testing on my own personal account led me to believe it a success.

Arizona State course enrollment regularly reaches triple digits. Despite the large enrollment numbers, the level of communication among students remain relatively low. Students often create Discord servers to keep in touch with classmates, but this requires each individual student to track down the invite link. The purpose of this project is to create an inviting chat service for students with minimal barriers of entry. This website, https://gibbl.io, offers a chat room for every class at ASU, making it simple for students to maintain communication.

In this paper, I introduce the fake news problem and detail how it has been exacerbated<br/>through social media. I explore current practices for fake news detection using natural language<br/>processing and current benchmarks in ranking the efficacy of various language models. Using a<br/>Twitter-specific benchmark, I attempt to reproduce the scores of six language models<br/>demonstrating their effectiveness in seven tweet classification tasks. I explain the successes and<br/>challenges in reproducing these results and provide analysis for the future implications of fake<br/>news research.

Artificial Intelligence is quickly growing to be an influential part of our daily lives. Due to this, we believe it is important to analyze how cultural perceptions can influence how we interact and develop technology. We decided to focus on India due to its large economic stature, cultural influence, and influence on the technology industry.

Artificial Intelligence is quickly growing to be an influential part of our daily lives. Due to this, we believe it is important to analyze how cultural perceptions can influence how we interact and develop technology<br/>We decided to focus on India due to its large economic stature, cultural influence, and influence on the technology industry.