Through this class project, I aimed to explore an aspect of Management Information Systems/Data Analysis that resonated with my interests and career goals. As a Marketing/MIS double major, I expressed interest in Sentiment Analysis, a process used to analyze textual data such as customer reviews and employee feedback forms, and its other business applications. The practical example of Nike’s brand monitoring following the Colin Kaepernick controversy contributed to my understanding of how sentiment analysis could be used to benefit even the most triumphant companies. The results of the data provided by Nike suggested that analyzing a dataset (in this case, customer sentiments on social media sites like Twitter) holistically proves to be more beneficial than focusing on the extremes of the data. In relation to the content covered in MIS 2502, Sentiment Analysis serves as an example of text-based analysis/text-mining, which is important considering the fact that much of the data found on the internet/social media is unstructured and numerous. In the end, the project helped me develop a more extensive understanding of Sentiment Analysis and its importance in relevant fields.