Honors Student Takes Aim at Harmful Messaging on Social Media
Computer Science major Matthew Morgan is currently working on his Honors Thesis designing platform-agnostic machine learning models to detect Sinophobia on social media.
With the advent of mainstream social networks such as Twitter, Facebook, and YouTube, the social media content now accounts for the majority of the content published on the Internet. Due to the content moderation policies on mainstream networks many alternative social media platforms such as Parler and Gab are becoming popular as they promote free speech. It is increasingly observable that social media presents enormous risks for individuals and communities as it used as a medium for cyberbullying, trolling, spreading fake news, and privacy abuse.
Matthew Morgan is a junior in the Department of Computing Sciences and student in the Honors College. He started his research about a year ago on analyzing user behavior on mainstream and alternative social media by looking at COVID-19 related data. He used machine learning models and text analysis tools to provide insights on the extent of toxicity and misinformation on mainstream vs alternative platforms. He presented his work at two conferences - the Consortium for Computing Sciences in Colleges in Northeast Region (CCSCNE) 2021 and the SUNY Undergraduate Research Conference (SURC) 2021. He was also part of the Summer Undergraduate Research Program (SURP) 2021.
Matthew Morgan is currently working on his Honors thesis by extending his work to design platform-agnostic machine learning models to detect Sinophobia on social media.