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Found 10 papers, 1 papers with code
BeSt: The Belief and Sentiment Corpus
We present the BeSt corpus, which records cognitive state: who believes what (i. e., factuality), and who has what sentiment towards what.
From Stance to Concern: Adaptation of Propositional Analysis to New Tasks and Domains
We develop a ground truth (GT) based on expert annotators and compare our concern detection output to GT, to yield 231% improvement in recall over baseline, with only a 10% loss in precision.
Learning to Plan and Realize Separately for Open-Ended Dialogue Systems
Achieving true human-like ability to conduct a conversation remains an elusive goal for open-ended dialogue systems.
Email Threat Detection Using Distinct Neural Network Approaches
This paper describes different approaches to detect malicious content in email interactions through a combination of machine learning and natural language processing tools.
Active Defense Against Social Engineering: The Case for Human Language Technology
We describe a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
The Panacea Threat Intelligence and Active Defense Platform
We describe Panacea, a system that supports natural language processing (NLP) components for active defenses against social engineering attacks.
Adaptation of a Lexical Organization for Social Engineering Detection and Response Generation
We present a paradigm for extensible lexicon development based on Lexical Conceptual Structure to support social engineering detection and response generation.
Detecting Asks in SE attacks: Impact of Linguistic and Structural Knowledge
Social engineers attempt to manipulate users into undertaking actions such as downloading malware by clicking links or providing access to money or sensitive information.
