Using natural language processing to analyse text data in behavioural science

S Feuerriegel, A Maarouf, D Bär, D Geissler… - Nature Reviews …, 2025 - nature.com
Abstract Language is a uniquely human trait at the core of human interactions. The
language people use often reflects their personality, intentions and state of mind. With the …

[HTML][HTML] Deception detection using ML and DL techniques: A systematic review

SA Prome, NA Ragavan, MR Islam… - Natural Language …, 2024 - Elsevier
Deception detection is a crucial concern in our daily lives, with its effect on social
interactions. The human face is a rich source of data that offers trustworthy markers of …

Comprehensive evaluation of eco-environmental resources in the main grain-producing areas of China

K Cheng, K He, N Sun, Q Fu - Ecological Informatics, 2023 - Elsevier
By evaluating the eco-environmental resources of China's major grain-producing regions,
the development status of the eco-environmental resources in major grain-producing …

EEG-based deception detection using weighted dual perspective visibility graph analysis

A Rahimi Saryazdi, F Ghassemi, Z Tabanfar… - Cognitive …, 2024 - Springer
Deception detection is a critical aspect across various domains. Integrating advanced signal
processing techniques, particularly in neuroscientific studies, has opened new avenues for …

[HTML][HTML] Lie detection algorithms disrupt the social dynamics of accusation behavior

A von Schenk, V Klockmann, JF Bonnefon, I Rahwan… - Iscience, 2024 - cell.com
Humans, aware of the social costs associated with false accusations, are generally hesitant
to accuse others of lying. Our study shows how lie detection algorithms disrupt this social …

Verbal lie detection using Large Language Models

R Loconte, R Russo, P Capuozzo, P Pietrini… - Scientific Reports, 2023 - nature.com
Human accuracy in detecting deception with intuitive judgments has been proven to not go
above the chance level. Therefore, several automatized verbal lie detection techniques …

Experimental economics for machine learning—a methodological contribution on lie detection

D Bershadskyy, L Dinges, MA Fiedler, A Al-Hamadi… - PloS one, 2024 - journals.plos.org
In this paper, we investigate how technology has contributed to experimental economics in
the past and illustrate how experimental economics can contribute to technological progress …

Pupillometry and autonomic nervous system responses to cognitive load and false feedback: an unsupervised machine learning approach

EI Alshanskaia, GV Portnova, K Liaukovich… - Frontiers in …, 2024 - frontiersin.org
Objectives Pupil dilation is controlled both by sympathetic and parasympathetic nervous
system branches. We hypothesized that the dynamic of pupil size changes under cognitive …

Micro-expression action unit recognition based on dynamic image and spatial pyramid

G Zhou, S Yuan, H Xing, Y Jiang, P Geng… - The Journal of …, 2023 - Springer
Most of the existing studies have focused on the expression recognition of micro-
expressions, while little research has been done on how to recognize the action units of …

ParaLBench: a Large-Scale Benchmark for Computational Paralinguistics over Acoustic Foundation Models

Z Zhang, W Xu, Z Dong, K Wang, Y Wu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Computational paralinguistics (ComParal) aims to develop algorithms and models to
automatically detect, analyze, and interpret non-verbal information from speech …