What We Mean When We Talk About Suffering—And Why Eric Cassell Should Not Have the Last Word
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Why Feelings Stray: Sources of Affective Misforecasting in Consumer Behavior Vanessa M
Why Feelings Stray: Sources of Affective Misforecasting in Consumer Behavior Vanessa M. Patrick, University of Georgia Deborah J. MacInnis, University of Southern California ABSTRACT drivers of AMF has considerable import for consumer behavior, Affective misforecasting (AMF) is defined as the gap between particularly in the area of consumer satisfaction, brand loyalty and predicted and experienced affect. Based on prior research that positive word-of-mouth. examines AMF, the current study uses qualitative and quantitative Figure 1 depicts the process by which affective misforecasting data to examine the sources of AMF (i.e., why it occurs) in the occurs (for greater detail see MacInnis, Patrick and Park 2005). As consumption domain. The authors find evidence supporting some Figure 1 suggests, affective forecasts are based on a representation sources of AMF identified in the psychology literature, develop a of a future event and an assessment of the possible affective fuller understanding of others, and, find evidence for novel sources reactions to this event. AMF occurs when experienced affect of AMF not previously explored. Importantly, they find consider- deviates from the forecasted affect on one or more of the following able differences in the sources of AMF depending on whether dimensions: valence, intensity and duration. feelings are worse than or better than forecast. Since forecasts can be made regarding the valence of the feelings, the specific emotions expected to be experienced, the INTRODUCTION intensity of feelings or the duration of a projected affective re- Before purchase: “I can’t wait to use this all the time, it is sponse, consequently affective misforecasting can occur along any going to be so much fun, I’m going to go out with my buddies of these dimensions. -
Classification of Human Emotions from Electroencephalogram (EEG) Signal Using Deep Neural Network
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 8, No. 9, 2017 Classification of Human Emotions from Electroencephalogram (EEG) Signal using Deep Neural Network Abeer Al-Nafjan Areej Al-Wabil College of Computer and Information Sciences Center for Complex Engineering Systems Imam Muhammad bin Saud University King Abdulaziz City for Science and Technology Riyadh, Saudi Arabia Riyadh, Saudi Arabia Manar Hosny Yousef Al-Ohali College of Computer and Information Sciences College of Computer and Information Sciences King Saud University King Saud University Riyadh, Saudi Arabia Riyadh, Saudi Arabia Abstract—Estimation of human emotions from [1]. Recognizing a user‘s affective state can be used to Electroencephalogram (EEG) signals plays a vital role in optimize training and enhancement of the BCI operations [2]. developing robust Brain-Computer Interface (BCI) systems. In our research, we used Deep Neural Network (DNN) to address EEG is often used in BCI research experimentation because EEG-based emotion recognition. This was motivated by the the process is non-invasive to the research subject and minimal recent advances in accuracy and efficiency from applying deep risk is involved. The devices‘ usability, reliability, cost- learning techniques in pattern recognition and classification effectiveness, and the relative convenience of conducting applications. We adapted DNN to identify human emotions of a studies and recruiting participants due to their portability have given EEG signal (DEAP dataset) from power spectral density been cited as factors influencing the increased adoption of this (PSD) and frontal asymmetry features. The proposed approach is method in applied research contexts [3], [4]. These advantages compared to state-of-the-art emotion detection systems on the are often accompanied by challenges such as low spatial same dataset. -
About Emotions There Are 8 Primary Emotions. You Are Born with These
About Emotions There are 8 primary emotions. You are born with these emotions wired into your brain. That wiring causes your body to react in certain ways and for you to have certain urges when the emotion arises. Here is a list of primary emotions: Eight Primary Emotions Anger: fury, outrage, wrath, irritability, hostility, resentment and violence. Sadness: grief, sorrow, gloom, melancholy, despair, loneliness, and depression. Fear: anxiety, apprehension, nervousness, dread, fright, and panic. Joy: enjoyment, happiness, relief, bliss, delight, pride, thrill, and ecstasy. Interest: acceptance, friendliness, trust, kindness, affection, love, and devotion. Surprise: shock, astonishment, amazement, astound, and wonder. Disgust: contempt, disdain, scorn, aversion, distaste, and revulsion. Shame: guilt, embarrassment, chagrin, remorse, regret, and contrition. All other emotions are made up by combining these basic 8 emotions. Sometimes we have secondary emotions, an emotional reaction to an emotion. We learn these. Some examples of these are: o Feeling shame when you get angry. o Feeling angry when you have a shame response (e.g., hurt feelings). o Feeling fear when you get angry (maybe you’ve been punished for anger). There are many more. These are NOT wired into our bodies and brains, but are learned from our families, our culture, and others. When you have a secondary emotion, the key is to figure out what the primary emotion, the feeling at the root of your reaction is, so that you can take an action that is most helpful. . -
Blending Between Occultism and Scientism in Vasile Voiculescu's
Article received on November 10, 2017 and accepted for publishing on February 18, 2018. ORIGINAL ARTICLES Blending between occultism and scientism in Vasile Voiculescu’s short stories Mirela Radu1 Abstract: Vasile Voiculescu (1884-1963), besides being a well-known writer, was also a prominent, much respected physician who practiced between the two world wars. He attended the courses of the Faculty of Letters and Philosophy in Bucharest for a year (1902-1903), but gave up on them in order to attend the Faculty of Medicine. The literary debut took place in 1912 in the journal Convorbiri literare. He published the first volume of lyrical poems in 1916 and in 1918 he was granted the Academy Award for lyrical volume From the Aurochs Country and other poems. In 1935 he became a member of the Academy of Sciences of Romania and in 1941 he received the National Poetry Prize. The following volumes of poems are: Ripeness (1921), Poems with Angels (1927), Destiny (1933), Ascent (1937), Gleams (1939). His work also includes a short story: The Demiurge (1943). Shakespeare's last imaginative sonnets in Vasile Voiculescu’s translation (1964), and the novel Zahei-The blind (1966), Sentimental Gymnastics (1972) are published posthumously. The present article is aimed at revealing the world of Voiculescu’s short stories. Keywords: medical studies, abyssal psychology, scientism, mystery, obscurity Although the most analyzed creator received new powers, as a sum of his life’s and part of Voiculescu’s work artistic experience by a high level of expression, in a seems to be his poetry, he veritable eruption if poetry, in verses and prose.” [2] proved his worth in the same The surprise comes from the chameleonic nature of manner in storytelling. -
Emotion Classification Using Physiological Signals
Emotion Classification Using Physiological Signals Byoung-Jun Park1, Eun-Hye Jang1, Myoung Ae Chung1, Sang-Hyeob Kim1*, Jin Hun Sohn2* 1IT Convergence Technology Research Laboratory, Electronics and Telecommunications Research Institute, Daejeon, 305-700 2Department of Psychology/Brain Research Institute, Chungnam National University, Daejeon, 305-765 ABSTRACT Objective: The aim of this study is to discriminate negative emotions, such as sadness, fear, surprise, and stress using physiological signals. Background: Recently, the main topic of emotion classification research is to recognize human’s feeling or emotion using various physiological signals. It is one of the core processes to implement emotional intelligence in human computer interaction (HCI) research. Method: Electrodermal activity (EDA), electrocardiogram (ECG), skin temperature (SKT), and photoplethysmography (PPG) are recorded and analyzed as physiological signals. And emotional stimuli are audio-visual film clips which have examined for their appropriateness and effectiveness through preliminary experiment. For classification of negative emotions, five machine learning algorithms, i.e., LDF, CART, SOM, and Naïve Bayes are used. Results: Result of emotion classification shows that an accuracy of emotion classification by CART (84.0%) was the highest and by LDA (50.7%) was the lowest. SOM showed emotion classification accuracy of 51.2% and Naïve Bayes was 76.2%. Conclusion: We could identify that CART was the optimal emotion classification algorithm for classifying 4 negative emotions (sadness, fear, surprise, and stress). Application: This result can be helpful to provide the basis for the emotion recognition technique in HCI. Keywords: Emotion classification, Negative emotion, Machine learning algorithm, Physiological signal 1. Introduction Nasoz, Alvarez, Lisetti, and Finkelstein, 2003). -
Healing Narrative: Ethics and Writing About Patients
Virtual Mentor American Medical Association Journal of Ethics July 2011, Volume 13, Number 7: 420-424. FROM THE EDITOR Healing Narrative—Ethics and Writing about Patients As Jack Coulehan and Anne Hawkins put it, “writing about patients is a growth industry” [1]. Recent years have seen an explosion of both fiction and nonfiction works written by physicians for a popular audience. Atul Gawande’s Complications, Pauline Chen’s Final Exam, and Danielle Ofri’s Singular Intimacies, all critically acclaimed and widely read, open a window into an experience that was once the sole province of those in medical training. These authors employ patient stories to convey poignant insights about what it is like to practice medicine. Neurologist Oliver Sacks’s classic Awakenings and more recent An Anthropologist on Mars also make use of patient stories, guiding his readers into the awe-inspiring world of the human mind through the unusual experiences of his patients. These powerful memoirs, however, move us to ask, whose stories are they telling? What are physicians’ responsibilities towards patients when they put them on paper? In this issue of Virtual Mentor, we explore the ethics of writing about patients and examine the sometimes conflicting, sometimes synergistic duties of physician and author. Sharing patient stories has always been a mainstay of medical education—every issue of Virtual Mentor begins with three clinical cases. This is not an arbitrary quirk but a reflection of a long tradition. Clinicians share patient stories on the wards, in grand rounds, in doctors’ lounges; they tell patient stories to medical trainees and teach them the language in which to tell these stories themselves. -
Examining Affective Forecasting and Its Practical and Ethical Implications
Examining Affective Forecasting and its Practical and Ethical Implications Emily Susan Brindley BSc Psychology 2009 Supervisor: Prof. David Clarke Contents Page Introduction 1 1. Affective Forecasting – What do we know? 1 2. Biases – Why people cannot predict their emotions accurately 3 2.1 Impact Bias 3 2.2 ‘Focalism’ 4 2.3 Immune Neglect 4 2.4 Dissimilar Context 4 3. The Self-Regulating Emotional System 5 4. Affective Forecasting Applied 6 4.1 Healthcare 6 4.2 Law 7 5. Can AFing be improved? 8 6. Ethics: Should people be taught to forecast more accurately? 10 Conclusions 12 References 13 Examining Affective Forecasting and its Practical and Ethical Implications Introduction Emotions are important in guiding thoughts and behaviour to the extent that they are used as heuristics (Slovic, Finucane, Peters & MacGregor, 2007), and are crucial in decision-making (Anderson, 2003). Affective forecasting (AFing) concerns an individual’s judgemental prediction of their or another’s future emotional reactions to events. It is suggested that “affective forecasts are among the guiding stars by which people chart their life courses and steer themselves into the future” (Gilbert, Pinel, Wilson, Blumberg & Wheatley, 1998; p.617), as our expected reactions to emotional events can assist in avoiding or approaching certain possibilities. We can say with certainty that we will prefer good experiences over bad (ibid); however AFing research demonstrates that humans are poor predictors of their emotional states, regularly overestimating their reactions. Further investigation of these findings shows that they may have critical implications outside of psychology. If emotions are so influential on behaviour, why are people poor at AFing? Furthermore, can and should individuals be assisted in forecasting their emotions? These issues, along with the function of AFing in practical applications, are to be considered and evaluated. -
OWNING YOUR FEELINGS Tips for Success
OWNING YOUR FEELINGS It can be easy to get caught up in your emotions as you’re feeling them. Most people don’t think about what emotions they are dealing with, but taking the time to really identify what you’re feeling can help you to better cope with challenging situations. The English language has over 3,000 words for Tips for success emotions. Allow yourself to feel. Sometimes there are societal pressures that encourage people to shut down their emotions, often expressed through People who are good at statements like, “Big girls don’t cry,” or “Man up.” These outdated ideas are being specific about harmful, not helpful. Everyone has emotionsthey are part of the human identifying and labeling experienceand you have every right to feel them, regardless of gender, their emotions are less sexual orientation, ethnicity, socio-economic status, race, political likely to binge drink, be affiliation or religion. physically aggressive, or selfinjure when Don’t ignore how you’re feeling. Most of us have heard the term “bottling up distressed. your feelings” before. When we try to push feelings aside without addressing them, they build strength and make us more likely to “explode” at some point in When schoolaged kids are the future. It may not always be appropriate to process your emotions at the taught about emotions for very moment you are feeling them, but try to do so as soon as you can. 20-30 minutes per week their social behavior and Talk it out. Find someone you trust that you can talk to about how you’re school performance feeling. -
Religious Perspectives on Human Suffering: Implications for Medicine and Bioethics
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Sydney eScholarship Postprint This is a pre-copyedited, author-produced PDF of an article accepted for publication in [Journal of Religion and Health] following peer review. The definitive publisher-authenticated version [Fitzpatrick SJ, Kerridge IH, Jordens CFC, Zoloth L, Tollefsen C, Tsomo KL, Jensen MP, Sachedina A, Sarma D. Religious perspectives on human suffering: Implications for medicine and bioethics. Journal of Religion and Health 2016; 55:159–173] is available online at http://link.springer.com/article/10.1007/s10943-015-0014-9 Please cite as: Fitzpatrick SJ, Kerridge IH, Jordens CFC, Zoloth L, Tollefsen C, Tsomo KL, Jensen MP, Sachedina A, Sarma D. Religious perspectives on human suffering: Implications for medicine and bioethics. Journal of Religion and Health 2016; 55:159–173. Religious perspectives on human suffering: Implications for medicine and bioethics Scott J FitzpatrickA,B, Ian H KerridgeB, Christopher F C JordensB , Laurie ZolothC, Christopher TollefsenD, Karma Lekshe TsomoE, Michael P JensenF, Abdulaziz SachedinaG, Deepak SarmaH (2015/16) ACentre for Rural and Remote Mental Health, University of Newcastle, Orange, Australia; BCentre for Values, Ethics and the Law in Medicine (VELiM), University of Sydney, Sydney, Australia; CCentre for Bioethics, Science and Society, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; DDepartment of Philosophy, University of South Carolina, Colombia, South Carolina, USA USA; EDepartment of Theology and Religious Studies, University of San Diego, San Diego, California, USA; FMoore Theological College, Sydney, Australia; GAli Vural Ak Centre for Global Islamic Studies, George Mason University, Fairfax, Virginia, USA; HReligious Studies, Case Western Reserve University, Cleveland, Ohio, USA. -
Emotion Classification Based on Biophysical Signals and Machine Learning Techniques
S S symmetry Article Emotion Classification Based on Biophysical Signals and Machine Learning Techniques Oana Bălan 1,* , Gabriela Moise 2 , Livia Petrescu 3 , Alin Moldoveanu 1 , Marius Leordeanu 1 and Florica Moldoveanu 1 1 Faculty of Automatic Control and Computers, University POLITEHNICA of Bucharest, Bucharest 060042, Romania; [email protected] (A.M.); [email protected] (M.L.); fl[email protected] (F.M.) 2 Department of Computer Science, Information Technology, Mathematics and Physics (ITIMF), Petroleum-Gas University of Ploiesti, Ploiesti 100680, Romania; [email protected] 3 Faculty of Biology, University of Bucharest, Bucharest 030014, Romania; [email protected] * Correspondence: [email protected]; Tel.: +40722276571 Received: 12 November 2019; Accepted: 18 December 2019; Published: 20 December 2019 Abstract: Emotions constitute an indispensable component of our everyday life. They consist of conscious mental reactions towards objects or situations and are associated with various physiological, behavioral, and cognitive changes. In this paper, we propose a comparative analysis between different machine learning and deep learning techniques, with and without feature selection, for binarily classifying the six basic emotions, namely anger, disgust, fear, joy, sadness, and surprise, into two symmetrical categorical classes (emotion and no emotion), using the physiological recordings and subjective ratings of valence, arousal, and dominance from the DEAP (Dataset for Emotion Analysis using EEG, Physiological and Video Signals) database. The results showed that the maximum classification accuracies for each emotion were: anger: 98.02%, joy:100%, surprise: 96%, disgust: 95%, fear: 90.75%, and sadness: 90.08%. In the case of four emotions (anger, disgust, fear, and sadness), the classification accuracies were higher without feature selection. -
ANXIETY DISORDERS in ADULTS the Disorders, Their Treatment and Prevention
Angstlidelser hos voksne, engelsk Information about ANXIETY DISORDERS IN ADULTS The disorders, their treatment and prevention Psykiatri og Social psykinfomidt.dk CONTENTS 03 What are anxiety disorders? 05 Why do some people suffer from anxiety disorders? 06 What happens in the brain when someone suffers from anxiety? 07 What types of anxiety disorders are there? 08 What are the symptoms of anxiety disorders? 10 Different degrees of anxiety disorders 11 How are they diagnosed? 12 What treatment is available for anxiety disorders? 15 What can be done to prevent anxiety disorders? 16 What can you do yourself if you are suffering from anxiety? 18 What can relatives do? 21 Where can you find more information? Anxiety disorders are the most common mental disorders in the population in the Western world. This brochure describes anxiety disorders, their specific characteristics as well as what they have in common, and their treatment. It also offers some advice to anxiety sufferers and their relatives. This brochure is for adults (age 18 and above), and it is mainly intended for people being treated for anxiety disorders by the psychiatric service in Region Midtjylland, and for their relatives. It is important for you and your relatives to learn about anxiety disorders. The more you know, the better you will be able to relate to the disorder when it occurs, and prevent relapses. Regional psychiatry in Region Midtjylland has six clinics offering outpatient treatment of anxiety disorders. We hope this brochure will help you and your relatives to become better informed about anxiety disorders. Kind regards The psychiatric service in Region Midtjylland Tingvej 15, 8800 Viborg Tel. -
On Emotion Specificity in Decision Making
Judgment and Decision Making, Vol. 3, No. 1, January 2008, pp. 18–27. On emotion specificity in decision making: Why feeling is for doing Marcel Zeelenberg∗1, Rob M. A. Nelissen1, Seger M. Breugelmans2, & Rik Pieters3 1 Department of Social Psychology and TIBER, Tilburg University 2 Department of Developmental, Clinical and Cross-cultural Psychology, Tilburg University 3 Department of Marketing and TIBER, Tilburg University Abstract We present a motivational account of the impact of emotion on decision making, termed the feeling-is-for-doing approach. We first describe the psychology of emotion and argue for a need to be specific when studying emotion’s impact on decision making. Next we describe what our approach entails and how it relates emotion, via motivation to behavior. Then we offer two illustrations of our own research that provide support for two important elements in our reasoning. We end with specifying four criteria that we consider to be important when studying how feeling guides our everyday doing. Keywords: emotion, decision making, motivation, action. 1 Introduction 1988). Bounded rationality may be helped by the exis- tence of emotion, because emotions restrict the size of the Most theories of rational decision making are descrip- consideration set and focus the decision maker on certain, tively implausible, especially if taken as process models. relevant aspects of the options (Hanoch, 2001). Emotions The idea that we take the time and invest the effort to pro- assign value to objects, aid the learning of how to ob- duce a list of advantages and disadvantages, or costs and tain those objects, and provide the motivation for doing benefits for all alternatives in each single decision and so (Gifford, 2002).