Graduation Semester and Year
Summer 2025
Language
English
Document Type
Thesis
Degree Name
Master of Science in Computer Science
Department
Computer Science and Engineering
First Advisor
Dr. Shirin Nilizadeh
Abstract
The increasing integration of technology into daily life has provided numerous benefits but also significant risks, particularly when exploited by malicious actors in cases of technology facilitated abuse (TFA). Per- petrators can misuse technology to monitor, control, and intimidate their partners, random strangers, etc. exacerbating cycles of abuse. From location tracking and cellphone surveillance to smart device manipula- tion, spyware, and doxing, digital tools have become powerful instruments for coercion and control. This research project investigates the role of technology in stalking and harassment by analyzing discussions on a relevant subreddit where victims share their experiences, strategies for coping, and concerns. By examining posts spanning from 2015 to 2024, we aim to identify the evolving tactics employed by abusers, the technological tools most frequently misused, and the responses of victims seeking support or intervention. The dataset consists of posts collected via Application Programming Interface (API) and an older data dump, with a subset manually labeled by two coders to capture key abuse patterns. Additionally, we employ Large Language Models (LLMs), such as Llama for automated labeling and feature extraction, using prompt engineering and chain-of-thought techniques to categorize abuse types, perpetrators, and victim responses. This hybrid approach enables scalable analysis while maintaining accuracy through human verification. Our findings will inform digital safety strategies and intervention efforts. We identified 9 categories of abuse, including Social media abuse (46%), Physical presence and harm abuse (35%), Location tracking abuse (29%), Device abuse (19%), Harassment and data sharing abuse (16%), Intimidation abuse (6%), Impersonation and IP abuse (6%), Cyberstalking abuse (5%), and Camera abuse (2.8%). Interestingly, we identified that the most mentioned technologies were social media (43%) followed by device (21%) and online account (10%). This shows the clear indication of TFA used by perpetrators to maliciously act against their victims. In addition to this, the most frequent perpetrator group was strangers to the victim, such as people from the internet or their neighborhood, appearing in 37% of all labeled posts. Surprisingly, perpetrators in 18.09% of the posts were found to be author of the posts themselves, either confessing their mistakes, sharing their experience, asking for advice, calling for harassment, etc.
Keywords
Technology-Facilitated Abuse (TFA), Intimate Partner Violence (IPV), Stalking, Reddit, Large Language Models (LLMs), Data Annotation/Labeling, Prompt Engineering, AsyncPRAW
Disciplines
Artificial Intelligence and Robotics | Cybersecurity | Data Science | Information Security | Social Media | Social Work
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Dandekar, Solomon G., "Technology-Facilitated Abuse (TFA): Analyzing Trends, Tactics, and Victim Responses on Reddit" (2025). Computer Science and Engineering Theses. 534.
https://mavmatrix.uta.edu/cse_theses/534
Included in
Artificial Intelligence and Robotics Commons, Cybersecurity Commons, Data Science Commons, Information Security Commons, Social Media Commons, Social Work Commons