arXiv subjects

Yefim Shulman

Publications and source records attributed to Yefim Shulman.

4 recordsLinked to original sources

arXiv2026

Discerning Authorship in Online Health Communities: Experience, Trust, and Transparency Implications for Moderating AI

For online health communities, community trust is paramount. Yet, advances in Large Language Models (LLMs) generating advice may erode this trust, especially if users cannot identify whether LLMs have been used. We investigate the feasibility of community-based detection of health advice authorship and how self-moderation of LLMs could help enhance advice utilization. In an online experiment, we evaluate people's ability to distinguish AI-generated from human-written advice across two health conditions, considering lived experience with a condition, AI-recognition training, and user attitudes towards transparency and trust around AI use. Our results indicate the need for transparency coupled with trust. We find little evidence of people's ability to discern advice authorship. However, we find a consistent effect of the health condition. Our qualitative findings identify unreliable signals, resulting in flawed heuristic evaluations of the advice. Our findings point to opportunities to improve the self-moderation of LLM-based AI and aid community-based AI moderation.

cs.HC↗

arXiv2022

Informing Users: Effects of Notification Properties and User Characteristics on Sharing Attitudes

Information sharing on social networks is ubiquitous, intuitive, and occasionally accidental. However, people may be unaware of the potential negative consequences of disclosures, such as reputational damages. Yet, people use social networks to disclose information about themselves or others, advised only by their own experiences and the context-invariant informed consent mechanism. In two online experiments (N=515 and N=765), we investigated how to aid informed sharing decisions and associate them with the potential outcomes via notifications. Based on the measurements of sharing attitudes, our results showed that the effectiveness of informing the users via notifications may depend on the timing, content, and layout of the notifications, as well as on the users' curiosity and rational cognitive style, motivating information processing. Furthermore, positive emotions may result in disregard of important information. We discuss the implications for user privacy and self-presentation. We provide recommendations on privacy-supporting system design and suggest directions for further research.

cs.HC↗

arXiv2020

Order of Control and Perceived Control over Personal Information

Focusing on personal information disclosure, we apply control theory and the notion of the Order of Control to study people's understanding of the implications of information disclosure and their tendency to consent to disclosure. We analyzed the relevant literature and conducted a preliminary online study (N = 220) to explore the relationship between the Order of Control and perceived control over personal information. Our analysis of existing research suggests that the notion of the Order of Control can help us understand people's decisions regarding the control over their personal information. We discuss limitations and future directions for research regarding the application of the idea of the Order of Control to online privacy.

cs.HC↗

arXiv2019

Is Privacy Controllable?

One of the major views of privacy associates privacy with the control over information. This gives rise to the question how controllable privacy actually is. In this paper, we adapt certain formal methods of control theory and investigate the implications of a control theoretic analysis of privacy. We look at how control and feedback mechanisms have been studied in the privacy literature. Relying on the control theoretic framework, we develop a simplistic conceptual control model of privacy, formulate privacy controllability issues and suggest directions for possible research.

cs.CY↗