Evolution of social media aggression

More than 500 undergraduates at the University of Delaware took part in the 2024 Summer Scholars program, conducting in-depth research or creative work alongside faculty or graduate student mentors. The Summer Scholars program can introduce students to a new field of interest or a future career path, or in the case of senior Blake Tran, confirm for her that she is exactly where she needs to be -- studying cognitive science at UD.

Ha (Blake) Tran spent the summer researching social media and its attentional and algorithmic bias towards negativity. Perhaps, not coincidentally, her own social media footprint is small, confined mostly to LinkedIn and other professional platforms. Tran is an honors cognitive science major, with minors in neuroscience and computer science. She conducted her research at UD's Impression Formation Social Neuroscience Lab, under the guidance of doctoral candidate Richa Gautam and Assistant Professor Jennifer Kubota, who holds joint appointments in the Department of Psychological and Brain Sciences and the Department of Political Science and International Relations.

"Since joining the lab, Blake has been an integral part of several projects using big data, including her honors thesis," said Kubota. "She has continued to develop her data science skills that will be essential tools for what I predict will be a successful future in graduate school."

UDaily talked with Tran about her project and the impact it has had on her future plans.

Tell us about your research.

Tran: I have been looking at the evolution of aggression on social media. We know it's harmful and it's widespread. In fact, according to the most recent survey from the Pew Research Center, four out of 10 adults in the U.S. reported having experienced some form of online harassment, and of these victims, 75 percent experienced it through social media.

We also know that people tend to have negativity bias, which is a cognitive tendency to pay more attention to negative and aversive stimuli. For example, research shows that negative and angry social media comments receive more attention and recognition compared to positive and fearful comments. This attentional bias is compounded further by websites' algorithms, which are designed to highlight content that has greater user engagement.

In my research, I wanted to find out more about the dynamics of online aggression - how it originates, spreads, and, sometimes, ends. For my methods, I used data scraping, a technique in which a computer program extracts data from output coming from another program. I selected two social media sites - Reddit and X - to scrape, using a combination of paid application programming interfaces (APIs) and web-scraping scripts. I did this during a set time frame and only collected posts that were written in English. Then, I coded and classified all this data.

Currently you are analyzing all this data before writing your senior thesis. Will you share some research preliminary findings?

Tran: Toxic posts incite toxicity. Additionally, the anonymity online and crowd effect of social media emboldens people to be more extreme in their posts.

How can those who use social media guard against being influenced by aggressive social media posts?

Tran: The best strategy is to disengage, i.e., not replying or liking the hateful comments/posts, blocking or reporting negative online accounts. Moreover, one might also rely on their support system, whether it is visiting or talking to friends, family, or counseling services about their situation.