Sequential Pattern Mining: Big Data Analysis in Mobile Gaming; Ethics of Facebook: Analyzing the Social Network and Global Leader

Hector Jr., Selwyn, School of Engineering and Applied Science, University of Virginia
Gorman, Michael, University of Virginia
Ji, Yangfeng, EN-Comp Science Dept, University of Virginia

My technical capstone is a data science project that attempts to make sense of a huge repository of activity data for players in a multiplayer mobile online game. The company that developed the mobile game was not able to analyze the data so my professors and I were then brought in to break down the data programmatically and develop models from it. My professors focused primarily on statistical analysis and I focused on data science programming. We used sequential pattern mining to look at users’ activity from login to logout. This analysis can be used to find which sets of actions are the best at predicting future actions. We then tied that gaming activity to spending activity in order to determine what actions were most frequent and most profitable.
My STS research paper gives an ethical analysis of Facebook’s business practices. I was particularly interested in Facebook because it is one of the most successful internet companies while also being one of the most infamous. It developed from my original prospectus which was similar but I wanted to explore not only highlight their culture but also determine what led them to their decision-making and how their decision-making, in turn, influenced society. I did this by studying three of their controversies since 2016 and looking for patterns across those incidences. I then applied various STS frameworks to further explore these controversies and determine how they can occur in successful companies. Ultimately, the thesis offers insights into the consequences that can result from the communications the internet provides.
Both my projects are related to practical software engineering. My capstone applies software to a business situation and extracts unique insights that can only be found through programming. My research paper then demonstrates that powerful technology also can have repercussions on users across the world and that these social repercussions are just as important as the engineering behind a product. The theme around doing them both together is that technology can lead to incredible new heights.

BS (Bachelor of Science)
Sequential Pattern Mining, Data Science, Utilitarianism, Normalized Deviance

School of Engineering and Applied Sciences.
Bachelor of Science in Computer Science
Technical Advisor: Yangfeng Ji
STS Advisor: Michael Gorman

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