7 citations · 24 across the 25 of their papers we have counts for
26 papers
Demonstrably Informed Consent in Privacy Policy Flows: Evidence from a Randomized Experiment
Qian Ma, Aditya Majumdar, Sarah Rajtmajer +1
Privacy policies govern how personal data is collected, used, and shared. Yet, in most privacy-policy consent flows, agreement is operationalized as a single click at the end of a…
Human-AI Collaboration for Estimating Scientific Replicability
Tatiana Chakravorti, Robert Fraleigh, Timothy Fritton +7
Determining whether published scientific findings can successfully be replicated is a long-standing challenge in the empirical sciences. Existing approaches for replicability asses…
Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generation
Xinyu Wang, Sai Koneru, Wenbo Zhang +3
Recent advances in large language models (LLMs) have enabled the large-scale generation of highly fluent and deceptive news-like content. While prior work has often treated fake ne…
Silence and Noise: Self-censorship and Opinion Expression on Social Media
Xinyu Wang, Emma Carpenetti, Bruce Desmarais +1
Unlike the more observable phenomenon of group opinion reinforcement, self-censorship online has received comparatively less attention. Our goal in this work is to dissect the phen…
Context Selection for Hypothesis and Statistical Evidence Extraction from Full-Text Scientific Articles
Sai Koneru, Jian Wu, Sarah Rajtmajer
Extracting hypotheses and their supporting statistical evidence from full-text scientific articles is central to the synthesis of empirical findings, but remains difficult due to d…
Evaluating Evidence Grounding Under User Pressure in Instruction-Tuned Language Models
Sai Koneru, Elphin Joe, Christine Kirchhoff +2
In contested domains, instruction-tuned language models must balance user-alignment pressures against faithfulness to the in-context evidence. To evaluate this tension, we introduc…
Beyond Detection: Governing GenAI in Academic Peer Review as a Sociotechnical Challenge
Tatiana Chakravorti, Pranav Narayanan Venkit, Sourojit Ghosh +1
Generative AI tools are increasingly entering academic peer review workflows, raising questions about fairness, accountability, and the legitimacy of evaluative judgment. While the…
ReplicatorBench: Benchmarking LLM Agents for Replicability in Social and Behavioral Sciences
Bang Nguyen, Dominik Soós, Qian Ma +8
The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on the computational aspect of thi…
Pedagogical Friction in Password Creation
Qian Ma, Yingfan Zhou, Shubhang Kaushik +6
Users often make security- and privacy-relevant decisions without a clear understanding of the rules that govern safe behavior. We introduce pedagogical friction, a design approach…
Effect of AI Performance, Risk Perception, and Trust on Human Dependence in Deepfake Detection AI system
Yingfan Zhou, Ester Chen, Manasa Pisipati +2
Synthetic images, audio, and video can now be generated and edited by Artificial Intelligence (AI). In particular, the malicious use of synthetic data has raised concerns about pot…
Social Scientists on the Role of AI in Research
Tatiana Chakravorti, Xinyu Wang, Pranav Narayanan Venkit +3
The integration of artificial intelligence (AI) into social science research practices raises significant technological, methodological, and ethical issues. We present a community-…
A Tale of Two Identities: An Ethical Audit of Human and AI-Crafted Personas
Pranav Narayanan Venkit, Jiayi Li, Yingfan Zhou +2
As LLMs (large language models) are increasingly used to generate synthetic personas particularly in data-limited domains such as health, privacy, and HCI, it becomes necessary to…
Can Third-parties Read Our Emotions?
Jiayi Li, Yingfan Zhou, Pranav Narayanan Venkit +4
Natural Language Processing tasks that aim to infer an author's private states, e.g., emotions and opinions, from their written text, typically rely on datasets annotated by third-…
Have LLMs Reopened the Pandora's Box of AI-Generated Fake News?
Xinyu Wang, Wenbo Zhang, Sai Koneru +5
With the rise of AI-generated content spewed at scale from large language models (LLMs), genuine concerns about the spread of fake news have intensified. The perceived ability of L…
Monolingual and Multilingual Misinformation Detection for Low-Resource Languages: A Comprehensive Survey
Xinyu Wang, Wenbo Zhang, Sarah Rajtmajer
In today's global digital landscape, misinformation transcends linguistic boundaries, posing a significant challenge for moderation systems. Most approaches to misinformation detec…
Embracing Transparency: A Study of Open Science Practices Among Early Career HCI Researchers
Tatiana Chakravorti, Sanjana Gautam, Sarah M. Rajtmajer
Many fields of science, including Human-Computer Interaction (HCI), have heightened introspection in the wake of concerns around reproducibility and replicability of published find…
The Failed Migration of Academic Twitter: A Case Study of Precocious Adopters
Xinyu Wang, Sai Koneru, Sarah Rajtmajer
Following changes in Twitter's ownership in 2022 and subsequent changes to content moderation policies, many in academia looked to move their discourse elsewhere and migration to M…
The Unappreciated Role of Intent in Algorithmic Moderation of Social Media Content
Xinyu Wang, Sai Koneru, Pranav Narayanan Venkit +2
As social media has become a predominant mode of communication globally, the rise of abusive content threatens to undermine civil discourse. Recognizing the critical nature of this…
Can citations tell us about a paper's reproducibility? A case study of machine learning papers
Rochana R. Obadage, Sarah M. Rajtmajer, Jian Wu
The iterative character of work in machine learning (ML) and artificial intelligence (AI) and reliance on comparisons against benchmark datasets emphasize the importance of reprodu…
Inside the echo chamber: Linguistic underpinnings of misinformation on Twitter
Xinyu Wang, Jiayi Li, Sarah Rajtmajer
Social media users drive the spread of misinformation online by sharing posts that include erroneous information or commenting on controversial topics with unsubstantiated argument…
An Audit on the Perspectives and Challenges of Hallucinations in NLP
Pranav Narayanan Venkit, Tatiana Chakravorti, Vipul Gupta +5
We audit how hallucination in large language models (LLMs) is characterized in peer-reviewed literature, using a critical examination of 103 publications across NLP research. Throu…
Reproducibility, Replicability, and Transparency in Research: What 430 Professors Think in Universities across the USA and India
Tatiana Chakravorti, Sai Dileep Koneru, Sarah Rajtmajer
In the past decade, open science and science of science communities have initiated innovative efforts to address concerns about the reproducibility and replicability of published s…
Integrating measures of replicability into scholarly search: Challenges and opportunities
Chuhao Wu, Tatiana Chakravorti, John Carroll +1
Challenges to reproducibility and replicability have gained widespread attention, driven by large replication projects with lukewarm success rates. A nascent work has emerged devel…
Perspectives from India: Opportunities and Challenges for AI Replication Prediction to Improve Confidence in Published Research
Tatiana Chakravorti, Chuhao Wu, Sai Koneru +1
Over the past decade, a crisis of confidence in scientific literature has gained attention, particularly in the West. In response, we have seen changes in policy and practice among…