Gared Ramirez, a senior majoring in computer science and statistics, is the author of a white paper, titled Fake News Detection with Headlines.
“Fake news has increasingly become a problem due to the rising use of the internet and social media. On top of that, many people skim the headlines without delving into the full article,” said Ramirez. “I believe it is important to be able to distinguish sources of fake and misleading news to ensure that misinformation does not erode trust in credible sources.”
Ramirez’ paper was the final element of his senior capstone project with Associate Teaching Professor Elizabeth McGuffey. Meng Li, the Noah Harding Assistant Professor of Statistics, served as his project advisor.
Ramirez presented his paper on Friday, Dec. 8, 2023. The paper was subsequently selected the following week for the CoFES White Paper Series.
For this project, Ramirez implemented five machine learning models (naive Bayes, logistic regression, decision tree, random forest, and support vector machine) and compared their accuracies when classifying fake news based on article headlines. He used measures such as term frequency-inverse document frequency and sentiment scores, as predictors in developing his models.
The models were trained using both a benchmark dataset and a dataset with full articles and headlines. In his results, Ramirez found that naive Bayes consistently performed best on both datasets with accuracies of 64.40 percent and 92.56 percent, respectively.
Ramirez is interested in software engineering fields where he can make a meaningful impact and leverage his skills in computer science and statistics. He is particularly drawn to cybersecurity following two summer internships as a software engineer in cloud security with Microsoft in Redmond, WA, and one summer with Bill.com in Palo Alto, CA.
While at Rice, he was a teaching assistant for the Department of Computer Science and was heavily involved with Rice’s chapter of the Society of Hispanic Professional Engineers.
- Shawn Hutchins, Communications and Marketing Specialist
