Abstract

Doping scandals can have a lasting effect on both athletes’ and organizations’ reputations, causing  athletes to lose money and fans to lose trust in the organi- zations that govern their favorite  sports. This paper investigates the impact a doping scandal can have on an athlete’s reputation by  conducting a case study on Jannik Sinner, one of the top tennis players in the world, who  ultimately accepted a suspension after testing positive for performance-enhancing drugs, despite  being unintentionally exposed. Using data sourced from YouTube comments on tennis-related videos, a fine-tuned  Mistral-7B-Instruct-v0.3 model with a classification head was used to carry out stance detection to  investigate the stance of fans towards Sin- ner over time, classifying comments as guilty  (believing Sinner intentionally cheated) or non guilty (supporting innocence, neutral, or  irrelevant). Our model achieved strong performance on non guilty comments (F1=0.97) but only  moderate precision and recall on guilty ones (0.71, 0.72), struggling with sarcasm, indirect  accusations, and case-specific references. Analyzing 843,005 comments and focusing on those  spanning the 20 months post-scandal, the re- sults show a downward trend in the percentage of  guilty comments (Kendall’s τ = -0.829), dropping from 2̃7.9% to 1̃.15%, supporting our hypothesis  that doubters decrease over time. However, key events like Sinner’s settlement and certain major  tournament appearances can temporarily reignite discussion. The results also confirmed that fans  revisit older videos to discuss new doping allegations. These findings demonstrate that the effects  of a doping scandal slowly fade over time but persist for an extended period, and this paper of-  fers a generalizable framework for examining similar cases across sports. This study highlights the  potential value of social-media-based sta   tection in informing anti-doping policies and communication strategies.

Publication Date

5-6-2026

Document Type

Thesis

Student Type

Graduate

Degree Name

Software Engineering (MS)

Department, Program, or Center

Software Engineering, Department of

College

Golisano College of Computing and Information Sciences

Advisor

Ashique KhudaBukhsh

Advisor/Committee Member

Larry Kiser

Advisor/Committee Member

Christian Newman

Campus

RIT – Main Campus

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