Headshot of me. Unfortunately, I did not have the chance to take one during the semester.
Author: Ananya Vangoor | Major: Computer Science, Mathematics | Semester: Spring 2025
Hello! I am Ananya Vangoor, a student in the College of Engineering. My mentor was Dr. Susan Gauch, a professor in the Department of Computer Science and Computer Engineering. I received funding for Spring 2025. My research explored creating a tool that would identify whether specific digital communities lean towards meritocracy or luck when it comes to success in the workplace environment.
Traditionally, social scientists collected information about people’s attitudes towards work (and many other topics) through the General Social Surveys (GSS). However, these surveys face significant limitations such as a limited number of questions, infrequent administration, high costs, small sample sizes, and difficulty measuring specific subgroups. As a result, there is growing interest among researchers in finding more efficient ways to measure trending topics and large user groups. This has led to the exploration of neural networks as a tool for understanding public sentiment, rather than relying solely on traditional surveys.
My research was a partnership between the Sociology and Computer Science departments. The end goal was to utilize this tool to understand the sentiments of communities that neural network may not have been trained on. This is the concept of transfer learning. We have trained our model with certain topics, but we are interested in testing it against related, but different topics. The topics we wanted to test against included liberals and conservatives. Using the tool I developed, I observed that liberal communities tended to emphasize luck while conservative communities leaned more toward meritocracy.
Coming to how I chose the topic and my mentor, I spoke with a couple of professors throughout my sophomore year to understand the type of research they were conducting and whether they were interested in taking on an Honors student. I enjoyed speaking with Dr. Susan Gauch, and I started being mentored by one of her Master’s students during the second semester of my Junior year. I spoke with three of her Master’s students, but I liked talking with Luka Greenway and enjoyed the work she was doing. My research followed the work done by Luka, which is how I ended up with this topic. My suggestions would be to start exploring research opportunities early and talk to as many professors as possible to make the best decision.
Throughout this research journey, I have learned that it is a different type of learning. Compared to the classroom setting where you will have a correct answer in the end, when conducting research you are exploring areas that may have seen little to no prior investigation. Since neural networks was a topic that was new to me, I asked numerous questions and set up biweekly meetings with my mentor. During these meetings, we discussed my progress, outlined next steps, and addressed any challenges or obstacles I encountered. I would also ask my mentor Luka if I had any questions as she explored this area of research before me and had some experience.
I had the opportunity to present my research at the Undergraduate Research Symposium in the Arkansas Union. It was my first research conference, and I thoroughly enjoyed it. A few of my friends along with some faculty came over to learn more about my research. It was a good experience since it taught me how to explain what I have done in the past year in a few minutes. I also learned how to explain concepts to people without a computer science background.
After graduation, I will be joining Capital One as a software engineer, and I am excited to continue learning and growing in the field. In a few years, I plan to pursue a Master’s degree. Though I haven’t decided on a specific area yet, that decision will be guided by the evolving tech industry.