48 citations · 79 across the 10 of their papers we have counts for
10 papers
Seeing Through AI's Lens: Enhancing Human Skepticism Towards LLM-Generated Fake News
Navid Ayoobi, Sadat Shahriar, Arjun Mukherjee
LLMs offer valuable capabilities, yet they can be utilized by malicious users to disseminate deceptive information and generate fake news. The growing prevalence of LLMs poses diff…
The Looming Threat of Fake and LLM-generated LinkedIn Profiles: Challenges and Opportunities for Detection and Prevention
Navid Ayoobi, Sadat Shahriar, Arjun Mukherjee
In this paper, we present a novel method for detecting fake and Large Language Model (LLM)-generated profiles in the LinkedIn Online Social Network immediately upon registration an…
Deception Detection with Feature-Augmentation by soft Domain Transfer
Sadat Shahriar, Arjun Mukherjee, Omprakash Gnawali
In this era of information explosion, deceivers use different domains or mediums of information to exploit the users, such as News, Emails, and Tweets. Although numerous research h…
Improving Phishing Detection Via Psychological Trait Scoring
Sadat Shahriar, Arjun Mukherjee, Omprakash Gnawali
Phishing emails exhibit some unique psychological traits which are not present in legitimate emails. From empirical analysis and previous research, we find three psychological trai…
A Domain-Independent Holistic Approach to Deception Detection
Sadat Shahriar, Arjun Mukherjee, Omprakash Gnawali
The deception in the text can be of different forms in different domains, including fake news, rumor tweets, and spam emails. Irrespective of the domain, the main intent of the dec…
Opinion Prediction with User Fingerprinting
Kishore Tumarada, Yifan Zhang, Fan Yang +3
Opinion prediction is an emerging research area with diverse real-world applications, such as market research and situational awareness. We identify two lines of approaches to the…