Are We Judgmental? Comparing CMSC320 Student vs. Reddit AITA Judgments
OC Study1. The Setup / TL;DR
We wanted to see if Computer Science students (specifically from CMSC320 sections) judge situations differently than the general Reddit r/AITA community. Students took a survey with modified AITA posts (rephrased as "Am I a Jerk?", sometimes with genders swapped). We compared their answers to the judgments found in the comments of the original Reddit posts.
Spoiler: Initial thoughts suggested similarity, but the actual data showed significant differences.
2. How We Did It (Data & Methods)
We grabbed comments from 5 original r/AITA posts that matched the survey questions. We automatically sorted comments based on the standard AITA acronyms: "YTA" (You're The Asshole), "NTA" (Not The Asshole), "INFO" (Information Needed), "NAH" (No Assholes Here), and "ESH" (Everyone Sucks Here).
The student survey data used different labels: "Not a jerk", "Mildly a jerk", and "Strongly a jerk". To compare apples-to-apples(ish), we converted both sets of labels into three simple categories:
- YTA: You're The Asshole / Strongly a jerk
- Neither: ESH / INFO / NAH / Mildly a jerk
- NTA: Not The Asshole / Not a jerk
Here's the conversion cheat sheet:
Original Source | Original Label | New Label |
---|---|---|
Reddit AITA | YTA | YTA |
ESH | Neither | |
INFO | Neither | |
NAH | Neither | |
NTA | NTA | |
CMSC320 Survey | Strongly a jerk | YTA |
Mildly a jerk | Neither | |
Not a jerk | NTA |
3. What We Found (Results)
After sorting and standardizing, we ran Chi-Squared tests. The results were clear: there was a statistically significant difference in how the CMSC320 students judged the situations compared to the Redditors on AITA for all five posts tested.
Here's the raw data and the test results (low p-values mean the difference is unlikely due to chance):
Wedding Question Results
Category | NTA | Neither | YTA |
---|---|---|---|
Reddit Wedding | 108 | 16 | 92 |
Student Wedding | 279 | 115 | 58 |
p-value = 2.92 × 10-19 |
Cat Question Results
Category | NTA | Neither | YTA |
---|---|---|---|
Reddit Cat | 291 | 253 | 203 |
Student Cat | 193 | 177 | 88 |
p-value = 0.00679 |
Child Support Question Results
Category | NTA | Neither | YTA |
---|---|---|---|
Reddit CS | 75 | 13 | 146 |
Student CS | 278 | 120 | 51 |
p-value = 2.42 × 10-44 |
Plane Babysit Question Results
Category | NTA | Neither | YTA |
---|---|---|---|
Reddit Plane | 453 | 127 | 575 |
Student Planes | 86 | 191 | 177 |
p-value = 9.37 × 10-46 |
Trust Fund Question Results
Category | NTA | Neither | YTA |
---|---|---|---|
Reddit Trust | 33 | 5 | 27 |
Student Trusts | 220 | 156 | 83 |
p-value = 9.05 × 10-7 |
YTA vs. NTA Ratio
This chart shows the ratio of YTA votes to NTA votes for each group and question. A higher bar means more "Asshole" judgments relative to "Not the Asshole" judgments.
Notice how the student ratio (Red bars) is lower in 4 out of 5 cases, suggesting they lean less towards the YTA judgment compared to Redditors (Blue bars).
4. Your Turn! How Do You Judge?
Read the brief scenarios below (based on the posts used in the study) and give your judgment. We'll show you how you compare to the CMSC320 students and the r/AITA commenters.
5. So, Are "We" Judgmental? (Conclusion)
Okay, there are some caveats (confounders). The way data was collected was different (survey vs comments), the original posts were public while the survey was private, Prof. Morawski's paraphrasing might have changed things, and the "Mildly a jerk" option added nuance not present in AITA votes.
BUT, even with those points, the evidence strongly suggests a real difference between how CMSC320 students and Redditors judged these scenarios. Importantly, in 4 out of 5 cases, the students were *less* likely to label someone the "asshole" (relative to NTA) compared to Redditors.
The Verdict: Based on this study, "we" (CMSC320 students) appear to be *less* judgmental than the r/AITA community, at least for these specific situations.
Future Ideas: To get better data, future surveys could match the AITA questions more closely, or maybe even analyze actual comments from students given Reddit accounts (ethically tricky!).
Comments
u/vonNeumann • 2 hr. ago
Wow, great paper
u/Einstein • 1 hr. ago
ikr
u/Gandalf • 1 hr. ago
Just incredible analysis