AIMC Topic: Emotions

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An android can show the facial expressions of complex emotions.

Scientific reports
Trust and rapport are essential abilities for human-robot interaction. Producing emotional expressions in the robots' faces is an effective way for that purpose. Androids can show human-like facial expressions of basic emotions. However, whether andr...

The advantages of lexicon-based sentiment analysis in an age of machine learning.

PloS one
Assessing whether texts are positive or negative-sentiment analysis-has wide-ranging applications across many disciplines. Automated approaches make it possible to code near unlimited quantities of texts rapidly, replicably, and with high accuracy. C...

Brain mapping, biomarker identification and using machine learning method for diagnosis of anxiety during emotional face in preschool children.

Brain research bulletin
BACKGROUND: Due to the importance and the consequences of anxiety, the goals of the current study are brain mapping, biomarker identification and the use of an assessment method for diagnosis of anxiety during emotional face in preschool children.

The role of psychological factors in predicting self-rated health: implications from machine learning models.

Psychology, health & medicine
Self-rated health (SRH) is a significant predictor of future health outcomes. Despite the contribution of psychological factors in individuals' subjective health assessments, prior studies of machine learning-based prediction models primarily focused...

A Fine-grained Hemispheric Asymmetry Network for accurate and interpretable EEG-based emotion classification.

Neural networks : the official journal of the International Neural Network Society
In this work, we propose a Fine-grained Hemispheric Asymmetry Network (FG-HANet), an end-to-end deep learning model that leverages hemispheric asymmetry features within 2-Hz narrow frequency bands for accurate and interpretable emotion classification...

DSTCNet: Deep Spectro-Temporal-Channel Attention Network for Speech Emotion Recognition.

IEEE transactions on neural networks and learning systems
Speech emotion recognition (SER) plays an important role in human-computer interaction, which can provide better interactivity to enhance user experiences. Existing approaches tend to directly apply deep learning networks to distinguish emotions. Amo...

An EEG-based emotion recognition method by fusing multi-frequency-spatial features under multi-frequency bands.

Journal of neuroscience methods
BACKGROUND: Recognition of emotion changes is of great significance to a person's physical and mental health. At present, EEG-based emotion recognition methods are mainly focused on time or frequency domains, but rarely on spatial information. Theref...

Sentiment analysis of tweets employing convolutional neural network optimized by enhanced gorilla troops optimization algorithm.

Scientific reports
Sentiment analysis has become a difficult and important task in the current world. Because of several features of data, including abbreviations, length of tweet, and spelling error, there should be some other non-conventional methods to achieve the a...

Direct perception of affective valence from vision.

Nature communications
Subjective feelings are thought to arise from conceptual and bodily states. We examine whether the valence of feelings may also be decoded directly from objective ecological statistics of the visual environment. We train a visual valence (VV) machine...

The public mental representations of deepfake technology: An in-depth qualitative exploration through Quora text data analysis.

PloS one
The advent of deepfake technology has raised significant concerns regarding its impact on individuals' cognitive processes and beliefs, considering the pervasive relationships between technology and human cognition. This study delves into the psychol...