Lexicons for Sentiment, Affect, and Connotation
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents
J Happiness Stud DOI 10.1007/s10902-009-9150-9 RESEARCH PAPER Measuring the Happiness of Large-Scale Written Expression: Songs, Blogs, and Presidents Peter Sheridan Dodds Æ Christopher M. Danforth Ó The Author(s) 2009. This article is published with open access at Springerlink.com Abstract The importance of quantifying the nature and intensity of emotional states at the level of populations is evident: we would like to know how, when, and why individuals feel as they do if we wish, for example, to better construct public policy, build more successful organizations, and, from a scientific perspective, more fully understand economic and social phenomena. Here, by incorporating direct human assessment of words, we quantify hap- piness levels on a continuous scale for a diverse set of large-scale texts: song titles and lyrics, weblogs, and State of the Union addresses. Our method is transparent, improvable, capable of rapidly processing Web-scale texts, and moves beyond approaches based on coarse categorization. Among a number of observations, we find that the happiness of song lyrics trends downward from the 1960s to the mid 1990s while remaining stable within genres, and that the happiness of blogs has steadily increased from 2005 to 2009, exhibiting a striking rise and fall with blogger age and distance from the Earth’s equator. Keywords Happiness Á Hedonometer Á Measurement Á Emotion Á Written expression Á Remote sensing Á Blogs Á Song lyrics Á State of the Union addresses 1 Introduction The desire for well-being and the avoidance of suffering arguably underlies all behavior (Argyle 2001; Layard 2005; Gilbert 2006; Snyder and Lopez 2009). -
Negative Emotions, Resilience and Mindfulness in Well-Being
Psychology and Behavioral Science International Journal ISSN 2474-7688 Research Article Psychol Behav Sci Int J Volume 13 Issue 2 - September 2019 Copyright © All rights are reserved by James Collard DOI: 10.19080/PBSIJ.2019.13.555857 The Role of Functional and Dysfunctional Negative Emotions, Resilience and Mindfulness in Well-Being B Shahzad and J Collard* School of Psychology, The Cairnmillar Institute, Australia Submission: August 01, 2019; Published: September 09, 2019 *Corresponding author: James Collard, School of Psychology, The Cairnmillar Institute, Melbourne, Australia Abstract This study sets out to investigate the binary model of emotions. It explores the relationships between suggested functional negative emotions and dysfunctional negative emotions with mindfulness, resilience, and well-being. The study was based on a sample of 104 adult participants. Results indicated that participants differentiated between proposed functional and dysfunctional negative emotion categories. Results of the structural equation modelling (SEM) demonstrated that functional negative emotions and dysfunctional negative emotions uniquely contributed to reduced well-being. The relationship of functional negative emotions to well-being was mediated by participants’ resilience levels. The relationship of dysfunctional negative emotions to well-being was mediated by participants’ resilience and mindfulness levels. SEM results indicated partial mediation, as the direct effect of functional and dysfunctional negative emotions on well-being was still -
Identifying Expressions of Emotions and Their Stimuli in Text
Identifying Expressions of Emotions and Their Stimuli in Text by Diman Ghazi Thesis submitted to the Faculty of Graduate and Postdoctoral Studies in partial fulfillment of the requirements for the Ph.D. degree in Computer Science School of Electrical Engineering and Computer Science Faculty of Engineering University of Ottawa c Diman Ghazi, Ottawa, Canada, 2016 Abstract Emotions are among the most pervasive aspects of human experience. They have long been of interest to social and behavioural sciences. Recently, emotions have attracted the attention of researchers in computer science and particularly in computational linguistics. Computational approaches to emotion analysis have also focused on various emotion modalities, but there is less effort in the direction of automatic recognition of the emotion expressed. Although some past work has addressed detecting emotions, detecting why an emotion arises is ignored. In this work, we explore the task of classifying texts automatically by the emotions expressed, as well as detecting the reason why a particular emotion is felt. We believe there is still a large gap between the theoretical research on emotions in psy- chology and emotion studies in computational linguistics. In our research, we try to fill this gap by considering both theoretical and computational aspects of emotions. Starting with a general explanation of emotion and emotion causes from the psychological and cognitive perspective, we clarify the definition that we base our work on. We explain what is feasible in the scope of text and what is practically doable based on the current NLP techniques and tools. This work is organized in two parts: first part on Emotion Expression and the second part on Emotion Stimulus. -
Understanding the Work of Pre-Abortion Counselors
Understanding the Work of Pre-abortion Counselors A dissertation presented to the faculty of The Patton College of Education of Ohio University In partial fulfillment of the requirements for the degree Doctor of Philosophy Jennifer M. Conte December 2013 © 2013 Jennifer M. Conte: All Rights Reserved. 2 This dissertation titled Understanding the Work of Pre-abortion Counselors by JENNIFER M. CONTE has been approved for the Department of Counseling and Higher Education and The Patton College of Education by Yegan Pillay Associate Professor of Counseling and Higher Education Renée A. Middleton Dean, The Patton College of Education 3 Abstract CONTE, JENNIFER M., Ph.D., December 2013, Counselor Education Understanding the Work of Pre-abortion Counselors Director of Dissertation: Yegan Pillay This qualitative study examined the experiences of individuals who work in abortion clinics as pre-abortion counselors. Interviewing was the primary method of inquiry. Although information regarding post-abortion distress is documented in the literature, pre-abortion counseling is rarely found in the literature. This study sought to fill a void in the literature by seeking to understand the experience of pre-abortion counselors. The documented experiences shared several themes such as a love for their job, having a non-judgmental attitude, and having a previous interest in reproductive health care. 4 Preface In qualitative methodology, the researcher is the instrument (Patton, 2002). Therefore, it is important to understand the lenses through which I am examining the phenomena of pre-abortion counseling. The vantage point that I offer is influenced by my experiences as a pre-abortion counselor. I have considered myself to be pro-choice ever since I can remember thinking about the topic of abortion. -
Preverbal Infants Match Negative Emotions to Events
Developmental Psychology © 2019 American Psychological Association 2019, Vol. 55, No. 6, 1138–1149 0012-1649/19/$12.00 http://dx.doi.org/10.1037/dev0000711 How Do You Feel? Preverbal Infants Match Negative Emotions to Events Ashley L. Ruba, Andrew N. Meltzoff, and Betty M. Repacholi University of Washington There is extensive disagreement as to whether preverbal infants have conceptual categories for different emotions (e.g., anger vs. disgust). In addition, few studies have examined whether infants have conceptual categories of emotions within the same dimension of valence and arousal (e.g., high arousal, negative emotions). The current experiments explore one aspect of infants’ ability to form conceptual categories of emotions: event-emotion matching. Three experiments investigated whether infants match different negative emotions to specific events. In Experiment 1, 14- and 18-month-olds were randomly assigned to 1 of 3 negative emotion conditions (Anger, Fear, or Disgust). Infants were familiarized with an Emoter interacting with objects in an anger-eliciting event (Unmet Goal) and a disgust-eliciting event (New Food). After each event, the Emoter expressed an emotion that was either congruent or incongruent with the event. Infants matched unmet goals to the expression of anger. However, neither age matched the expression of disgust to an event involving exposure to new food. To probe whether this was a design artifact, a revised New Food event and a fear-congruent event (Strange Toy) were created for Experiment 2. Infants matched the expression of disgust to the new food event, but they did not match fear to an event involving an unfamiliar object. -
Fear, Anger, and Risk
Journal of Personality and Social Psychology Copyright 2001 by the American Psychological Association, Inc. 2001. Vol. 81. No. 1, 146-159 O022-3514/01/$5.O0 DOI. 10.1037//O022-3514.81.1.146 Fear, Anger, and Risk Jennifer S. Lemer Dacher Keltner Carnegie Mellon University University of California, Berkeley Drawing on an appraisal-tendency framework (J. S. Lerner & D. Keltner, 2000), the authors predicted and found that fear and anger have opposite effects on risk perception. Whereas fearful people expressed pessimistic risk estimates and risk-averse choices, angry people expressed optimistic risk estimates and risk-seeking choices. These opposing patterns emerged for naturally occurring and experimentally induced fear and anger. Moreover, estimates of angry people more closely resembled those of happy people than those of fearful people. Consistent with predictions, appraisal tendencies accounted for these effects: Appraisals of certainty and control moderated and (in the case of control) mediated the emotion effects. As a complement to studies that link affective valence to judgment outcomes, the present studies highlight multiple benefits of studying specific emotions. Judgment and decision research has begun to incorporate affect In the present studies we follow the valence tradition by exam- into what was once an almost exclusively cognitive field (for ining the striking influence that feelings can have on normatively discussion, see Lerner & Keltner, 2000; Loewenstein & Lerner, in unrelated judgments and choices. We diverge in an important way, press; Loewenstein, Weber, Hsee, & Welch, 2001; Lopes, 1987; however, by focusing on the influences of specific emotions rather Mellers, Schwartz, Ho, & Ritov, 1997). To date, most judgment than on global negative and positive affect (see also Bodenhausen, and decision researchers have taken a valence-based approach to Sheppard, & Kramer, 1994; DeSteno et al, 2000; Keltner, Ells- affect, contrasting the influences of positive-affect traits and states worth, & Edwards, 1993; Lerner & Keltner, 2000). -
From Desire Coherence and Belief Coherence to Emotions: a Constraint Satisfaction Model
From desire coherence and belief coherence to emotions: A constraint satisfaction model Josef Nerb University of Freiburg Department of Psychology 79085 Freiburg, Germany http://www.psychologie.uni-freiburg.de/signatures/nerb/ [email protected] Abstract The model is able to account for the elicitation of discrete emotions using these five criteria. In the DEBECO archi- Appraisal theory explains the elicitation of emotional reactions as a consequence of subjective evaluations tecture, the five criteria evolve out of three basic principles: based on personal needs, goals, desires, abilities, and belief coherence, desire coherence and belief-desire coher- beliefs. According to the appraisal approach, each emo- ence. Based on these principles, which are all well sup- tion is caused by a characteristic pattern of appraisals, ported by empirical evidence from psychological research, and different emotions are associated with different ap- DEBECO also allows the representation of two elementary praisals. This paper presents the DEBECO architec- types of goals: approach goals and avoidance goals. The ture, a computational framework for modeling the ap- DEBECO architecture is implemented as a parallel con- praisal process. DEBECO is based upon three core straint satisfaction network and is an extension of Thagard’s coherence principles: belief coherence, desire coher- HOTCO model (Thagard, 2000, 2003; Thagard & Nerb, ence and belief-desire coherence. These three coher- 2002). ence mechanisms allow two elementary types of goals to be represented: approach and avoidance goals. By Within DEBECO, emotions are seen as valenced reac- way of concrete simulation examples, it is shown how tions to events, persons or objects, with their particular na- discrete emotions such as anger, pride, sadness, shame, ture being determined by the way in which the eliciting situ- surprise, relief and disappointment emerge out of these ation is construed (cf. -
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. -
The Lived Experience of Being Born Into Grief
The lived experience of being born into grief Michelle Holt A thesis submitted to Auckland University of Technology in partial fulfilment of the requirements of the degree of Doctor of Health Science (DHSc) 2018 School of Public Health and Psychosocial Studies Faculty of Health and Environmental Sciences Primary Supervisor: Dr Jacqueline Feather Abstract This study explores the meaning of the lived experience of being born into grief. Using a phenomenological hermeneutic methodology, informed by the writings of Martin Heidegger [1889-1976] and Hans-George Gadamer [1900-2002], this research provides an understanding of the lived experience of having been a baby when one or both parents were grieving (born into grief). The review of the literature identified physical effects of being born when a mother was stressed but no literature was found which discussed emotional effects that a baby may incur due to stress or grief of a parent. The notion of grief was explored and literature pertaining to early childhood adversity reviewed as a possible resource for bringing light to how it may be for babies born into grief. The literature indicated that possible long term complications such as rebellious behaviour, poor relationships, poor mental and physical health, could be a result of early adversity. The literature on understanding effects of grief from a conceptual perspective, rather than from the lived experience perspective, provided a platform for this study. In this study nine New Zealand participants told their stories about the grief situation they were born into and how they thought it had affected them. Data were gathered in the form of semi structured interviews which were audio recorded and transcribed verbatim. -
At Least 13 Dimensions Organize Subjective Experiences Associated with Music Across Different Cultures
What music makes us feel: At least 13 dimensions organize subjective experiences associated with music across different cultures Alan S. Cowena,1,2, Xia Fangb,c,1, Disa Sauterb, and Dacher Keltnera aDepartment of Psychology, University of California, Berkeley, CA 94720; bDepartment of Psychology, University of Amsterdam, 1001 NK Amsterdam, The Netherlands; and cDepartment of Psychology, York University, Toronto, ON M3J 1P3, Canada Edited by Dale Purves, Duke University, Durham, NC, and approved December 9, 2019 (received for review June 25, 2019) What is the nature of the feelings evoked by music? We investi- people hear a moving or ebullient piece of music, do particular gated how people represent the subjective experiences associated feelings—e.g., “sad,”“fearful,”“dreamy”—constitute the foun- with Western and Chinese music and the form in which these dation of their experience? Or are such feelings constructed representational processes are preserved across different cultural from more general affective features such as valence (pleasant vs. groups. US (n = 1,591) and Chinese (n = 1,258) participants listened unpleasant) and arousal (9, 11–15)? The answers to these to 2,168 music samples and reported on the specific feelings (e.g., questions not only illuminate the nature of how music elicits “ ”“ ” angry, dreamy ) or broad affective features (e.g., valence, subjective experiences, but also can inform claims about how the arousal) that they made individuals feel. Using large-scale statisti- brain represents our feelings (8, 15), how infants learn to rec- cal tools, we uncovered 13 distinct types of subjective experience ognize feelings in themselves and others (16), the extent to which associated with music in both cultures. -
Chinese Cultural Values and Chinese Language Pedagogy
CHINESE CULTURAL VALUES AND CHINESE LANGUAGE PEDAGOGY A Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Arts in the Graduate School of the Ohio State University By Bo Zhu, M.A. The Ohio State University Master’s Examination Committee Approved by Dr. Galal Walker, Adviser Dr. Mari Noda ________________________________ Adviser Graduate Program in East Asian Languages and Literatures Copyright @ 2008 Bo Zhu ABSTRACT Cultural values hold great control on people’s social behaviors. To become culturally competent, it is important for second language learners to understand primary cultural values in the target culture and to behave in accordance with those values. Cultural themes are the behavioral norms that people share in a society in pursuit of cultural values, which help learners relate what they learn to do with cultural values. The purpose of this study is to identify pedagogical cultural values and cultural themes in Chinese language education and propose a performance-based language curriculum, which integrates cultural values and cultural themes into language pedagogy. There are mainly three research questions discussed. First, what are the primary components in the Chinese cultural value system? Second, how is a cultural value manifest and managed in social behaviors? Third, how can a performance-based language curriculum integrate cultural values and cultural themes? This thesis analyzes the nature of cultural values and the components of Chinese cultural value system, with goals to identify pedagogical cultural values in Chinese language education. Seven cultural values are selected based on proposed criteria as primary pedagogical cultural themes in Chinese language education.