Modeling the Experience of Emotion

2010 ◽  
Vol 1 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Joost Broekens
Keyword(s):  
Computational Modeling ◽  
Affective Computing ◽  
Computational Models ◽  
Appraisal Theory ◽  
Content Change ◽  
Primary Focus ◽  
Computational Models Of Emotion ◽  
Research Initiatives ◽  
And Behavior ◽  
Do So

Affective computing has proven to be a viable field of research comprised of a large number of multidisciplinary researchers, resulting in work that is widely published. The majority of this work consists of emotion recognition technology, computational modeling of causal factors of emotion and emotion expression in virtual characters and robots. A smaller part is concerned with modeling the effects of emotion on cognition and behavior, formal modeling of cognitive appraisal theory and models of emergent emotions. Part of the motivation for affective computing as a field is to better understand emotion through computational modeling. In psychology, a critical and neglected aspect of having emotions is the experience of emotion: what does the content of an emotional episode look like, how does this content change over time, and when do we call the episode emotional. Few modeling efforts in affective computing have these topics as a primary focus. The launch of a journal on synthetic emotions should motivate research initiatives in this direction, and this research should have a measurable impact on emotion research in psychology. In this article, I show that a good way to do so is to investigate the psychological core of what an emotion is: an experience. I present ideas on how computational modeling of emotion can help to better understand the experience of motion, and provide evidence that several computational models of emotion already address the issue.

scholarly journals Modeling the Experience of Emotion

2012 ◽  
pp. 1-18 ◽  
Author(s):  
Joost Broekens
Keyword(s):  
Computational Modeling ◽  
Affective Computing ◽  
Computational Models ◽  
Appraisal Theory ◽  
Content Change ◽  
Primary Focus ◽  
Computational Models Of Emotion ◽  
Research Initiatives ◽  
And Behavior ◽  
Over Time

Affective computing has proven to be a viable field of research comprised of a large number of multidisciplinary researchers, resulting in work that is widely published. The majority of this work consists of emotion recognition technology, computational modeling of causal factors of emotion and emotion expression in virtual characters and robots. A smaller part is concerned with modeling the effects of emotion on cognition and behavior, formal modeling of cognitive appraisal theory and models of emergent emotions. Part of the motivation for affective computing as a field is to better understand emotion through computational modeling. In psychology, a critical and neglected aspect of having emotions is the experience of emotion: what does the content of an emotional episode look like, how does this content change over time and when do we call the episode emotional. Few modeling efforts in affective computing have these topics as a primary focus. The launch of a journal on synthetic emotions should motivate research initiatives in this direction, and this research should have a measurable impact on emotion research in psychology. In this paper, I show that a good way to do so is to investigate the psychological core of what an emotion is: an experience. I present ideas on how computational modeling of emotion can help to better understand the experience of emotion, and provide evidence that several computational models of emotion already address the issue.

scholarly journals Effect of emotionally toned Malay language sounds on the brain: a NIRS analysis

2019 ◽  
Vol 5 (1) ◽  
pp. 1-7
Author(s):  
Muhammad Nur Adilin Mohd Anuardi ◽  
Atsuko K. Yamazaki
Keyword(s):  
Language Processing ◽  
Affective Computing ◽  
Computational Models ◽  
Near Infrared ◽  
Positive Influence ◽  
Human Communication ◽  
Brain Areas ◽  
College Age ◽  
Recent Developments ◽  
Computational Models Of Emotion

Speech recognition features such as emotion have always been involved in human communication. With the recent developments in the communication methods, researchers have investigated artificial and emotional intelligence to improve communication. This has led to the emergence of affective computing, which deals with processing information pertaining to human emotions. This study aims to determine positive influence of language sounds containing emotion on brain function for improved communication. Twenty-seven college-age Japanese subjects with no prior exposure to the Malay language listened to emotionally toned and emotionally neutral sounds in the Malay language. Their brain activities were measured using near-infrared spectroscopy (NIRS) as they listened to the sounds. A comparison between different NIRS signals revealed that emotionally toned language sounds had a greater impact on brain areas associated with attention and emotion. On the contrary, emotionally neutral Malay sounds affected brain areas involved in working memory and language processing. These results suggest that emotionally-charged sounds initiate listeners’ attention and emotion recognition even when the listeners do not understand the language. The ability to interpret emotions presents challenges in computer systems and robotics; therefore, we hope that our results can be used for the development of computational models of emotion for autonomous robot research in the field of communication.

Insurgent Collaboration

2020 ◽  
Vol 9 (1) ◽  
pp. 106-110
Author(s):  
Linda E. Sánchez ◽  
Susan Bibler Coutin
Keyword(s):  
Central America ◽  
Educational Programs ◽  
Immigrant Communities ◽  
Research Model ◽  
Research Initiatives ◽  
Do So

Scholarship regarding those who are categorized as undocumented can put sanctuary principles into practice in research settings. To do so, scholars can conduct research in collaboration with immigrant communities, reject essentializing terminology, develop modes of sociality that challenge exclusion, and document the unofficial forms of sanctuary devised by members of immigrant communities. This research model is grounded in principles of accompaniment that were followed by 1980s activists who offered sanctuary to those fleeing wars in Central America. Examples of research initiatives and educational programs that follow such principles are presented.

Computing Possible Futures

2019 ◽  
Author(s):  
William B. Rouse
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computational Modeling ◽  
Mental Model ◽  
Data Analytics ◽  
Computational Models ◽  
Senior Managers ◽  
Interactive Visualizations ◽  
Use Of Models ◽  
Better Than

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.

High on God

2019 ◽  
Author(s):  
James Wellman ◽  
Katie Corcoran ◽  
Kate Stockly
Keyword(s):  
Dark Side ◽  
Senior Pastor ◽  
Interaction Ritual ◽  
Group Loyalty ◽  
Worship Services ◽  
Homo Duplex ◽  
Nationally Representative ◽  
Primary Focus ◽  
Two Sides ◽  
Do So

Humans are homo duplex, seeking to be individuals but knowing this is only possible in communities. Thus, humans struggle to integrate these two sides of their nature. Megachurches have been enormously successful at resolving this struggle. How do they do it, and what is it about their structure and rituals that makes so many feel as if they are high on God? The affective energies and emotional valences that characterize religious ecstasy are the primary focus of our study of megachurches. Empirically, humans want and desire forms of what Randall Collins calls “emotional energy.” Drawing on extensive qualitative and quantitative data on twelve nationally representative megachurches, we identify six desires that megachurches evoke and meet: acceptance, awe and spiritual stimulation, reliable leadership, deliverance, purpose, and solidarity in a community of like-minded others. Megachurches satisfy these desires through co-presence—being in the presence of other desiring people—a shared mood achieved through powerful musical worship services, a mutual focus of attention on the charismatic senior pastor who acts as an emotional charging agent, transformative altar calls, service opportunities, and small-group participation. This interaction ritual chain solidifies attendees’ commitment and group loyalty, and keeps them coming back to be recharged. Megachurches also have a dark side: they are known for their highly publicized scandals often involving malfeasance of the senior pastor. After examining the positive and negative sides to megachurches, we conclude that they successfully meet the desire of humans to flourish as individuals and to do so in a group.

scholarly journals Appraisal patterns as predictors of emotional expressions and shares on political social networking sites

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Thomas Zerback ◽  
Dominique S. Wirz
Keyword(s):  
Social Networking ◽  
Political Communication ◽  
Social Networking Sites ◽  
Emotional Reactions ◽  
Appraisal Theory ◽  
Emotional Expressions ◽  
Automated Content Analysis ◽  
And Behavior ◽  
Attitudes And Behavior ◽  
Citizens Attitudes

Emotions are considered important drivers of the diffusion of messages on social networking sites. Therefore, emotion-eliciting political communication yields the potential to reach broad audiences and to influence citizens’ attitudes and behavior. In this study, we investigate message characteristics that potentially trigger emotional reactions on part of the users of political social networking pages and test if this fosters the diffusion of political content in the network. Based on appraisal theory, we employ a manual coding scheme to identify appraisal dimensions in political parties’ Facebook posts that should trigger sadness or anger. We subsequently combine the manual codings with information of the users’ reactions to the respective posts, which we gathered using an automated content analysis. More specifically, we determine (1) if posts that include sadness or anger appraisals are associated with the corresponding emotional reactions in the form of emojis and (2) if these posts are shared more often.

scholarly journals Omics and Computational Modeling Approaches for the Effective Treatment of Drug-Resistant Cancer Cells

2021 ◽  
Vol 12 ◽  
Author(s):  
Hae Deok Jung ◽  
Yoo Jin Sung ◽  
Hyun Uk Kim
Keyword(s):  
Machine Learning ◽  
Computational Modeling ◽  
Cancer Treatment ◽  
Effective Treatment ◽  
Cancer Cells ◽  
Computational Models ◽  
Omics Data ◽  
Drug Resistant ◽  
Learning Models ◽  
Machine Learning Models

Chemotherapy is a mainstream cancer treatment, but has a constant challenge of drug resistance, which consequently leads to poor prognosis in cancer treatment. For better understanding and effective treatment of drug-resistant cancer cells, omics approaches have been widely conducted in various forms. A notable use of omics data beyond routine data mining is to use them for computational modeling that allows generating useful predictions, such as drug responses and prognostic biomarkers. In particular, an increasing volume of omics data has facilitated the development of machine learning models. In this mini review, we highlight recent studies on the use of multi-omics data for studying drug-resistant cancer cells. We put a particular focus on studies that use computational models to characterize drug-resistant cancer cells, and to predict biomarkers and/or drug responses. Computational models covered in this mini review include network-based models, machine learning models and genome-scale metabolic models. We also provide perspectives on future research opportunities for combating drug-resistant cancer cells.

Computing, Philosophy and Reality

2010 ◽  
pp. 238-252
Author(s):  
Joseph Brenner
Keyword(s):  
Quantum Computing ◽  
Cellular Automata ◽  
Computational Modeling ◽  
Computational Models ◽  
Mathematical Structure ◽  
Quantum Superposition ◽  
Information Theoretic ◽  
Process View ◽  
New Interpretation ◽  
The Universe

The conjunction of the disciplines of computing and philosophy implies that discussion of computational models and approaches should include explicit statements of their underlying worldview, given the fact that reality includes both computational and non-computational domains. As outlined at ECAP08, both domains of reality can be characterized by the different logics applicable to them. A new “Logic in Reality” (LIR) was proposed as best describing the dynamics of real, non-computable processes. The LIR process view of the real macroscopic world is compared here with recent computational and information-theoretic models. Proposals that the universe can be described as a mathematical structure equivalent to a computer or by simple cellular automata are deflated. A new interpretation of quantum superposition as supporting a concept of paraconsistent parallelism in quantum computing and an appropriate ontological commitment for computational modeling are discussed.

Politeness and Etiquette Modeling

2011 ◽  
pp. 387-411 ◽  
Author(s):  
Christopher A. Miller ◽  
Tammy Ott ◽  
Peggy Wu ◽  
Vanessa Vakili
Keyword(s):  
Computational Models ◽  
Decision Aids ◽  
Central Element ◽  
Universal Theory ◽  
Subjective Perceptions ◽  
Patterns Of Behavior ◽  
Perception Model ◽  
Effective Decision ◽  
Coarse Model ◽  
And Behavior

If culture is expressed in the patterns of behavior, values and expectations of a group, then a central element in the practical modeling and understanding of culture is the expression of politeness and its roles in governing and influencing behavior. The authors have been developing computational models of “politeness” and its role in power and familiarity relationships, urgency, indebtedness, etc. Such a model, insofar as it extends to human-machine interactions, will enable better and more effective decision aids. This model, based on a universal theory of human politeness, links aspects of social context (power and familiarity relationships, imposition, character), which have culture-specific values, to produce expectations about the use of polite, redressive behaviors (also culturally defined). The authors have linked this “politeness perception” model to a coarse model of decision making and behavior in order to predict influences of politeness on behavior and attitudes. This chapter describes the algorithm along with results from multiple validation experiments: two addressing the model’s ability to predict perceived politeness and two predicting the impact of perceived politeness on compliance behaviors in response to directives. The authors conclude that their model tracks well with subjective perceptions of American cultural politeness and that its predictions broadly anticipate and explain situations in which perceived politeness in a directive yields improved affect, trust, perceived competence, subjective workload, and compliance, though somewhat decreased reaction time. The model proves better at accounting for the effects of social distance than for power differences.

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