Dissertations, Theses, and Capstone Projects
Date of Degree
2-2020
Document Type
Thesis
Degree Name
M.A.
Program
Linguistics
Advisor
Kyle Gorman
Subject Categories
Computational Linguistics
Keywords
online ratings, interface design, teacher ratings
Abstract
In June 2018, RateMyProfessors.com (RMP), a popular website for students to leave professor reviews, removed a controversial feature known as the “chili pepper” which allowed students to rate their professors as “hot” or “not hot.” Though past research has rigorously analyzed the correlation of the chili pepper with higher ratings in other categories (Felton, Mitchell, and Stinson, 2004; Felton et al., 2008), none has measured the effect of the removal of the chili pepper on the text content submitted by students. While it is a positive step that the chili pepper has been removed, text commentary on teacher attractiveness persists and is submitted to the site through the “additional comments” text field. Using text classification and ensemble learning methods, we identify these reviews and their perpetuation after the chili pepper with high accuracy. Our analysis of 358,000 reviews from RMP representing a cross-section of professors from private and public universities across the U.S. finds two important trends: (1) the frequency of attractiveness comments in teacher reviews has been in decline over an eight-year period; and (2) the removal of the chili pepper from the web interface is significantly associated with this declining trend. These findings validate the activism behind asking web companies like RMP to remove online rating features that might seem entertaining, but foster workplace harassment and other harms.
Recommended Citation
Waller, Angie, "Ghost Peppers: Using Ensemble Models to Detect Professor Attractiveness Commentary on RateMyProfessors.com" (2020). CUNY Academic Works.
https://academicworks.cuny.edu/gc_etds/3642