UT student Michelle Xia attempted to determine student sentiments toward topics such as COVID-19 in a recent study using data from the UT and Texas A&M University subreddits.
Xia used a system of artificial intelligence that analyzes text samples to compute meaning to evaluate how students felt about eight topics, including COVID-19, housing, classes and social justice. She compiled the 1,348 most recent text entries from the UT subreddit and included a post’s title, body and comments.
Xia, a management information systems senior, said one of the main motivations for her to write this article was to pursue a personal project and to use her knowledge of the AI system.
“I’m taking this class right now, MIS 373, User-Generated Content Analysis, and I was just thinking I can actually apply these techniques and … get a bunch of valuable information,” Xia said.
Xia compared the topic of COVID-19 between the two universities, and she found UT students had more negative sentiments toward COVID-19 based on the content of their entries.
People like linguistics senior Cutter Dalton use the UT subreddit and responded to Xia’s article with comments and upvotes on Reddit.
“Having an actual analysis of the language that is actually used regarding UT on the subreddit, you can actually mathematically see how people feel, and that’s really cool,” Dalton said. “I’m not sure if it would represent how UT (as a whole) feels, given the dataset is based off of the subreddit, so you might have overrepresentation of one group of students.”
Xia said she addressed the potential concern with the bias of only representing students in the subreddit and she could have more in-depth data with more time or resources. Xia said this project was mostly a comparison between the UT and A&M subreddits.
“I was a little surprised to see that people tend to associate engineering more strongly with A&M, but the A&M school spirit and culture do seem to be stronger, anecdotally speaking, which may curate a more well-defined reputation,” Xia said in the article. “On the other hand, UT-Austin is strongly associated with COVID.”
Psychology professor James Pennebaker said he found parts of Xia’s analysis interesting.
“In some ways, the most interesting findings that Michelle had are the A&M and UT data, where you can see that A&M and UT students are really focusing on different topics, and that’s quite interesting,” Pennebaker said.
