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

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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