Control Attention differences for tasks with affective content

2011 ◽  
Author(s):  
M. A. Quiroga ◽  
J. Privado ◽  
F. J. Roman
Keyword(s):  
Affective Content

The Healing Magic of Joy: Understanding Magic as a Metaphor for Positive Emotion in The Secret Garden

2015 ◽  
Vol 8 (2) ◽  
pp. 127-141
Author(s):  
Margrete Lamond
Keyword(s):  
Positive Affect ◽  
Scientific Method ◽  
Positive Emotion ◽  
Literary Analysis ◽  
Data Driven ◽  
The Novel ◽  
Top Down ◽  
Affective Content ◽  
The Secret Garden ◽  
Biological Nature

Literary analysis tends to be conceptual and top-down driven. Data-driven analysis, although it belongs more to the domain of scientific method, can nevertheless sometimes reveal elements of narrative that conceptual readings may fall short of identifying. In critiques of Burnett's The Secret Garden, the children's return to health is generally understood to be the result of their interactions with nature. Some readings add the power of storytelling as a healing force in the novel. Burnett's concept of magic has tended to be treated with uneasy abstractions, and the influence of affect on health remains open for further investigation. This article bases its argument on data-driven analysis that charts how affective content in the novel occurs in conjunction with references to magic. It identifies the narrative significance of negative allusions to nature and how concepts of magic occur alongside representations of positive affect, and suggests that the magic of healing in The Secret Garden is not the transforming power of biological nature, nor the transforming power of storytelling, but the transforming power of surprise, wonder and happiness in conjunction with all these factors. Positive affect represents the essence of what Burnett means by magic.

Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence

AI Magazine ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 67-78
Author(s):  
Guy Barash ◽  
Mauricio Castillo-Effen ◽  
Niyati Chhaya ◽  
Peter Clark ◽  
Huáscar Espinoza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Cyber Security ◽  
Question Answering ◽  
Intent Recognition ◽  
Affective Content ◽  
Learning Plan ◽  
Dialog System ◽  
Affective Content Analysis ◽  
Games And Simulations

The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.

Structured Gaussian Process Regression of Music Mood

2020 ◽  
Vol 176 (2) ◽  
pp. 183-203
Author(s):  
Santosh Chapaneri ◽  
Deepak Jayaswal
Keyword(s):  
Gaussian Process ◽  
Computational Cost ◽  
Gaussian Process Regression ◽  
Gaussian Mixture ◽  
Feature Representation ◽  
Affective Content ◽  
Variational Bayesian Inference ◽  
Benchmark Datasets ◽  
Valence And Arousal ◽  
Structured Regression

Modeling the music mood has wide applications in music categorization, retrieval, and recommendation systems; however, it is challenging to computationally model the affective content of music due to its subjective nature. In this work, a structured regression framework is proposed to model the valence and arousal mood dimensions of music using a single regression model at a linear computational cost. To tackle the subjectivity phenomena, a confidence-interval based estimated consensus is computed by modeling the behavior of various annotators (e.g. biased, adversarial) and is shown to perform better than using the average annotation values. For a compact feature representation of music clips, variational Bayesian inference is used to learn the Gaussian mixture model representation of acoustic features and chord-related features are used to improve the valence estimation by probing the chord progressions between chroma frames. The dimensionality of features is further reduced using an adaptive version of kernel PCA. Using an efficient implementation of twin Gaussian process for structured regression, the proposed work achieves a significant improvement in R2 for arousal and valence dimensions relative to state-of-the-art techniques on two benchmark datasets for music mood estimation.

scholarly journals The Content of Nostalgic Memories Among People Living with Dementia

2021 ◽  
pp. 009141502110241
Author(s):  
Sanda Ismail ◽  
Emily Dodd ◽  
Gary Christopher ◽  
Tim Wildschut ◽  
Constantine Sedikides ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Positive Affect ◽  
Self Esteem ◽  
Healthy Adults ◽  
Word Count ◽  
Autobiographical Memories ◽  
Affective Content

Although dementia may affect the reliability of autobiographical memories, the psychological properties of nostalgic memories may be preserved. We compared the content of nostalgic ( n = 36) and ordinary ( n = 31) narratives of 67 participants living with dementia. Narratives were rated according to their self-oriented, social, and existential properties, as well as their affective content. Social properties and affective content were assessed using a linguistic word count procedure. Compared to the ordinary narratives described in the control condition, nostalgic narratives described a typical events, expressed more positive affect, and had more expressions of self-esteem and self-continuity. They were also rated higher on companionship, connectedness and the closeness of relationships, and reflected life as being meaningful. Despite their cognitive impairment, people living with dementia experience nostalgia in similar ways to cognitively healthy adults, with their nostalgic narratives containing self-oriented, social, and existential properties.

scholarly journals Comparative Time Series Analysis of Perceptual Responses to Electroacoustic Music

2012 ◽  
Vol 29 (4) ◽  
pp. 359-375 ◽  
Author(s):  
Freya Bailes ◽  
Roger T. Dean
Keyword(s):  
Time Series ◽  
Sound Intensity ◽  
Electroacoustic Music ◽  
Affective Content ◽  
Musical Expertise ◽  
Perceived Change ◽  
Time Series Analyses ◽  
Time Perceptions ◽  
The Relationship ◽  
Acoustic Measure

this study investigates the relationship between acoustic patterns in contemporary electroacoustic compositions, and listeners' real-time perceptions of their structure and affective content. Thirty-two participants varying in musical expertise (nonmusicians, classical musicians, expert computer musicians) continuously rated the affect (arousal and valence) and structure (change in sound) they perceived in four compositions of approximately three minutes duration. Time series analyses tested the hypotheses that sound intensity influences listener perceptions of structure and arousal, and spectral flatness influences perceptions of structure and valence. Results suggest that intensity strongly influences perceived change in sound, and to a lesser extent listener perceptions of arousal. Spectral flatness measures were only weakly related to listener perceptions, and valence was not strongly shaped by either acoustic measure. Differences in response by composition and musical expertise suggest that, particularly with respect to the perception of valence, individual experience (familiarity and liking), and meaningful sound associations mediate perception.

scholarly journals When Words Hurt: Affective Word Use in Daily News Coverage Impacts Mental Health

2018 ◽  
Vol 9 ◽  
Author(s):  
Jolie B. Wormwood ◽  
Madeleine Devlin ◽  
Yu-Ru Lin ◽  
Lisa Feldman Barrett ◽  
Karen S. Quigley
Keyword(s):  
Mental Health ◽  
Depressive Symptoms ◽  
Computational Linguistics ◽  
News Coverage ◽  
Physical Symptoms ◽  
Physiological Reactivity ◽  
Data Set ◽  
Affective Content ◽  
Aversive Stimuli ◽  
The Impact

Media exposure influences mental health symptomology in response to salient aversive events, like terrorist attacks, but little has been done to explore the impact of news coverage that varies more subtly in affective content. Here, we utilized an existing data set in which participants self-reported physical symptoms, depressive symptoms, and anxiety symptoms, and completed a potentiated startle task assessing their physiological reactivity to aversive stimuli at three time points (waves) over a 9-month period. Using a computational linguistics approach, we then calculated an average ratio of words with positive vs. negative affective connotations for only articles from news sources to which each participant self-reported being exposed over the prior 2 weeks at each wave of data collection. As hypothesized, individuals exposed to news coverage with more negative affective tone over the prior 2 weeks reported significantly greater physical and depressive symptoms, and had significantly greater physiological reactivity to aversive stimuli.

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