Rr. Nefriana

PhD Student · Information Science

University of Pittsburgh,
School of Computing and Information

Rr. Nefriana PhD Student

Studying how extremist communities evolve online, gender gaps in hateful content, and AI-driven interventions against misinformation — combining computational methods with social theory to build a safer information environment.

Computational Social Science Online Extremism Network Analysis NLP & LLMs Online Psychology Health Misinformation Gender & Hate Online Python · R · SQL Human Behavior

Selected Publications

Featured Work
ICWSM 2026Lead Author

Leader-driven or Leaderless: How Participation Structure Sustains Engagement and Shapes Narratives in Online Hate Communities

Rr. Nefriana, Muheng Yan, Rebecca Hwa, Yu-Ru Lin

Extremist communities increasingly rely on social media to sustain and amplify divisive discourse. This study analyzes ten years of Facebook activity by hate groups related to the Israel–Palestine conflict, focusing on anti-Semitic and Islamophobic ideologies. We find that higher participation centralization is associated with greater user engagement, suggesting key actors sustain group activity over time. Our narrative frame detection models reveal centralized Islamophobic groups use more uniform messaging, while centralized anti-Semitic groups show greater framing diversity — providing a foundation for tailored counter-strategies.

ICWSM 2024Co-Author

Classifying Conspiratorial Narratives at Scale: False Alarms and Erroneous Connections

Ahmad Diab, Rr. Nefriana, Yu-Ru Lin

Not all online discussions about conspiracy theories promote them — some aim to debunk them. This work establishes a classification scheme based on authors' perspectives, expressed through narrative elements or references to known theories. We train a BERT-based model and compare it to GPT, finding significant flaws in GPT's logical reasoning. The first large-scale classification of active conspiracy-related Reddit forums finds that only one-third of posts are genuinely conspiratorial — illuminating how LLMs handle nuanced contextual comprehension tasks.

More Publications & Presentations

Media Coverage

Featured Work
About

I am a PhD student in Information Science at the University of Pittsburgh, studying how extremist online communities evolve, gender gaps in the circulation of hateful content online, and how AI-driven interventions can counter health misinformation. My research combines computational methods — network analysis, NLP, and large language models — with social theory to understand what makes harmful content persuasive. As an Indonesian woman, first-generation graduate student, and mother, I bring a perspective that is often absent from tech research.

Education
PhD in Information Science
University of Pittsburgh
Pittsburgh, USA
Expected 2028 · GPA 4.00
MS in Information System Management
Bina Nusantara University
Jakarta
2018
BSc in Computational Statistics
Politeknik Statistika STIS
Jakarta
2012
Honors & Awards
Winner, Pitt Cyber Accelerator Grant2025
People's Choice Award, 3MT Competition — School of Computing and Information, Pitt2025
Best Visualization Award, PhD Poster Slam — School of Computing and Information, Pitt2024
Technical Skills
Programming & Data
PythonRSQL ServerMySQL
AI & NLP
NLPLLMsBERTGPT
Research Methods
Network ScienceComp. Social ScienceData MiningStatistics
Visualization & Tools
GephiNetwork VisualizationData Visualization
Leadership & Service
Program Committee Member — Ex-ASE 20252025
Peer Reviewer — ACM TSC, ICWSM, The Web Conf (WWW), Ex-ASE2023–Present
Vice President, SCI Doctoral Guild — University of Pittsburgh2024–2025
Vice President, PERMIAS (Indonesian Student Association) — University of Pittsburgh2022–2024
Languages
EnglishIndonesianJavaneseArabic (limited)

Let's
Connect.

Open to collaborations
rr.nefriana@pitt.edu